[ECOLOG-L] Webinar: Improve your Regression Models with Key Machine Learning Methods (no charge)

[Lisa Solomon]

Improve your Regression Models with Key Machine Learning Methods

*   Methods Discussed: MARS Non-linear Regression, Gradient Boosting, 
Random Forests
*   LIVE OR ON-DEMAND: Tuesday, October 17th 10AM - 11AM PDT, 1PM EDT

*   ON-DEMAND: If time is inconvenient, please register and we will send 
you the recording
*   Duration: 45 minutes followed by Q&A
*   Cost: Complimentary
*   Session 3 of the Webinar Series: Learn How to Make Machine Learning 
Work.  Each session is stand-alone

Registration: https://hubs.ly/H08y4ty0
* Alternative Link: 
http://info.salford-systems.com/datascience101webinarseries


ABSTRACT:

Machine learning may sound like an overwhelmingly complicated concept rather 
than a data-driven method to extract insights that drive future business 
decisions. To fully utilize machine learning, we first need to understand the 
benefits to our organization, and the techniques to create models based on 
questions we need to answer.  In this webinar series, we will show you how to 
easily and automatically apply complex algorithms to data in real world 
applications.



ALL SESSIONS IN THE WEBINAR SERIES: (Each webinar is stand-alone)

* ON-DEMAND: Data Science: Proven Value in a Variety of Industries

* ON-DEMAND: Improve your Classification Models with Key Machine 
Learning Methods (CART Decision Trees, Gradient Boosting, Random Forests) 
(OCTOBER 10)

* NEXT WEEK: Improve your Regression Models with key Machine Learning 
methods (MARS non-linear regression, Gradient Boosting, Random Forests) 
(OCTOBER 17)

* Real-world demonstration for the beginner modeler (OCTOBER 24)

* Real-world demonstration for advanced modelers (OCTOBER 31)



Who should attend:

* Beginners will learn the basics. Data Science techniques that 
encompass the foundation of data modeling- key methods, building a predictive 
model, extracting value from complex datasets.

* Advanced Modelers will continue to evolve their ability to leverage 
the power of data science. Improve both regression and classification models by 
utilizing automated features that shorten the time to create an accurate model. 
 We also cover how to better handle missing data, outliers, significant 
interrelationships among variables that are otherwise hard to capture.

Registration: https://hubs.ly/H08y4ty0
* Alternative Link: 
http://info.salford-systems.com/datascience101webinarseries

[ECOLOG-L] Webinar: Improve your Classification Models with Key Machine Learning Methods (no charge)

[Lisa Solomon]

Improve your Classification Models with Key Machine Learning Methods

  *   Methods Discussed: CART Decision Trees, Gradient Boosting, Random Forests
  *   LIVE OR ON-DEMAND: Tuesday, October 10th 10AM - 11AM PDT, 1PM EDT

  *   ON-DEMAND: If time is inconvenient, please register and we will send you 
the recording
  *   Duration: 45 minutes followed by Q&A
  *   Cost: Complimentary
  *   Session 2 of the Webinar Series: Learn How to Make Machine Learning Work. 
 Each session is stand-alone

Registration: https://hubs.ly/H08y4ty0

* Alternative Link: 
http://info.salford-systems.com/datascience101webinarseries


ABSTRACT:
Machine learning may sound like an overwhelmingly complicated concept rather 
than a data-driven method to extract insights that drive future business 
decisions. To fully utilize machine learning, we first need to understand the 
benefits to our organization, and the techniques to create models based on 
questions we need to answer.  In this webinar series, we will show you how to 
easily and automatically apply complex algorithms to data in real world 
applications.

ALL SESSIONS IN THE WEBINAR SERIES: (Each webinar is stand-alone)

* ON-DEMAND: Data Science: Proven Value in a Variety of Industries

* NEXT WEEK: Improve your Classification Models with Key Machine 
Learning Methods (CART Decision Trees, Gradient Boosting, Random Forests) 
(OCTOBER 10)

* Improve your Regression Models with key Machine Learning methods 
(MARS non-linear regression, Gradient Boosting, Random Forests) (OCTOBER 17)

* Real-world demonstration for the beginner modeler (OCTOBER 24)

* Real-world demonstration for advanced modelers (OCTOBER 31)


Who should attend:

* Beginners will learn the basics. Data Science techniques that 
encompass the foundation of data modeling- key methods, building a predictive 
model, extracting value from complex datasets.

* Advanced Modelers will continue to evolve their ability to leverage 
the power of data science. Improve both regression and classification models by 
utilizing automated features that shorten the time to create an accurate model. 
 We also cover how to better handle missing data, outliers, significant 
interrelationships among variables that are otherwise hard to capture.

Registration: https://hubs.ly/H08y4ty0

* Alternative Link: 
http://info.salford-systems.com/datascience101webinarseries

[ECOLOG-L] Webinar Series: Data Science 101: Learn How to Make Machine Learning Work (no charge)

[Lisa Solomon]

Webinar Series: Learn How to Make Machine Learning Work

LIVE OR ON-DEMAND

  *   LIVE: Tuesdays, October 3, 10, 17, 24, 31st, 10AM - 11AM PDT, 1PM EDT
  *   ON-DEMAND: If times are inconvenient, please register and we will send 
you the recordings
  *   Duration: 45 minutes followed by Q&A
  *   Cost: Complimentary

Registration: https://hubs.ly/H08y4ty0

Alternative Link: 
http://info.salford-systems.com/datascience101webinarseries


ABSTRACT:
Machine learning may sound like an overwhelmingly complicated concept rather 
than a data-driven method to extract insights that drive future business 
decisions. To fully utilize machine learning, we first need to understand the 
benefits to our organization, and the techniques to create models based on 
questions we need to answer.  In this webinar series, we will show you how to 
easily and automatically apply complex algorithms to data in real world 
applications.

SESSIONS: (Each webinar is stand-alone)

  *   Data Science: Proven Value in a Variety of Industries (OCTOBER 3)
  *   Improve your Classification Models with Key Machine Learning Methods 
(CART Decision Trees, Gradient Boosting, Random Forests) (OCTOBER 10)
  *   Improve your Regression Models with key Machine Learning methods (MARS 
non-linear regression, Gradient Boosting, Random Forests) (OCTOBER 17)
  *   Real-world demonstration for the beginner modeler (OCTOBER 24)
  *   Real-world demonstration for advanced modelers (OCTOBER 31)


Who should attend:

  *   Beginners will learn the basics. Data Science techniques that encompass 
the foundation of data modeling- key methods, building a predictive model, 
extracting value from complex datasets.
  *   Advanced Modelers will continue to evolve their ability to leverage the 
power of data science. Improve both regression and classification models by 
utilizing automated features that shorten the time to create an accurate model. 
 We also cover how to better handle missing data, outliers, significant 
interrelationships among variables that are otherwise hard to capture.

Registration: https://hubs.ly/H08y4ty0

Alternative Link: 
http://info.salford-systems.com/datascience101webinarseries

[ECOLOG-L] Webinar: Improve Your Regression with CART and Gradient Boosting

[Lisa Solomon]

Webinar: Improve Your Regression with CART and Gradient Boosting

LIVE OR ON-DEMAND

* LIVE: Thursday, February 16th, 10AM - 11AM PST, 1PM EST

* ON-DEMAND: If the time is inconvenient, please register and we will 
send you a recording

* Duration: 45 minutes

* Cost: Complimentary

* Real-world dataset, step-by-step instructions, hands-on option


Registration: http://hubs.ly/H06365x0

Alternative Link: 
http://info.salford-systems.com/improve-you-regression-cart-randomforests




ABSTRACT:
In this webinar we'll introduce you to a powerful tree-based machine learning 
algorithm called gradient boosting. Gradient boosting often outperforms linear 
regression, Random  Forests, and CART. Boosted trees automatically handle 
variable selection, variable interactions, nonlinear relationships, outliers, 
and missing values.

We'll see that CART decision trees are the foundation of gradient boosting and 
discuss some of the advantages of boosting versus a Random Forest. We will 
explore the gradient boosting algorithm and discuss the most important modeling 
parameters like the learning rate, number of terminal nodes, number of trees, 
loss functions, and more. We will demonstrate using an implementation of 
gradient boosting (TreeNet(r) Software) to fit the model and compare the 
performance to a linear regression model, a CART tree, and a Random Forest.

Who should attend:

* Attend if you want to implement data science techniques even without 
a data science, programming, or even an advanced statistical background.

* Attend if you want to understand why data science techniques are so 
important for analysts.


Registration: http://hubs.ly/H06365x0

Alternative Link: 
http://info.salford-systems.com/improve-you-regression-cart-randomforests

[ECOLOG-L] Webinar: Improve Your Regression with CART and RandomForests

[Lisa Solomon]

Webinar: Improve Your Regression with CART and RandomForests

LIVE OR ON-DEMAND

* LIVE: Thursday, January 26th, 10AM - 11AM PST, 1PM EST

* ON-DEMAND: If the time is inconvenient, please register and we will 
send you a recording

* Duration: 45 minutes

* Cost: Complimentary

* Real-world dataset, step-by-step instructions, hands-on option


Registration: http://hubs.ly/H05XfP60

Alternative Link: 
http://info.salford-systems.com/improve-you-regression-cart-randomforests




ABSTRACT:
In this webinar we'll introduce you to two tree-based machine learning 
algorithms, CART decision trees and RandomForests. We will discuss the 
advantages of tree-based techniques including their ability to automatically 
handle variable selection, variable interactions, nonlinear relationships, 
outliers, and missing values. We'll explore the CART algorithm, bootstrap 
sampling, and the Random Forest algorithm (all with animations) and compare 
their predictive performance using a real world dataset.

Who should attend:

* Attend if you want to implement data science techniques even without 
a data science, programming, or even an advanced statistical background.

* Attend if you want to understand why data science techniques are so 
important for analysts.


Registration: http://hubs.ly/H05XfP60

Alternative Link: 
http://info.salford-systems.com/improve-you-regression-cart-randomforests

[ECOLOG-L] Webinar Wednesday: The Evolution of Classification, a 2-Part Series (no charge)

[Lisa Solomon]

Webinar Wednesday: The Evolution of Classification, a 2-Part Series (no charge)
• Join us for a special 2-part webinar about Modern Classification Techniques, 
presented by Mikhail Golovnya, Senior Scientist. 
• In this webinar we will show machine learning and data science algorithms for 
Classification.

REGISTRATION LINK: http://hubs.ly/H04Mm1t0
• Alternative link:  
http://info.salford-systems.com/evolution-of-classification-2016
• Can’t Come? Sign up and receive the recording!

We will cover:
• Logistic Regression and Discriminant Analysis to Neural Networks and Support 
Vector Machine
• From Nearest Neighbor Classifiers to Trees, Forests, and Boosted Models

Live or On-demand:
Part 1: October 19 @ 10am Pacific, Logistic Regression and Discriminant 
Analysis to Neural Networks and Support Vector Machine
Part 2: October 26 @ 10am Pacific, From Nearest Neighbor Classifiers to Trees, 
Forests, and Boosted Models

REGISTRATION LINK: http://hubs.ly/H04Mm1t0
• Alternative link:  
http://info.salford-systems.com/evolution-of-classification-2016
• Can’t Come? Sign up and receive the recording!

[ECOLOG-L] Webinar: Improve Your Regression with Modern Regression Analysis Techniques

[Lisa Solomon]

Improve Your Regression with Modern Regression Analysis Techniques

*Part 1: July 27 @ 10:00 am PDT: Linear, Nonlinear, 
Regularized, GPS, LARS, LASSO, Elastic Net, MARS(r)

*Part 2: August 10 @ 10am PDT: TreeNet(r) Gradient 
Boosting, RandomForests(r), ISLE(tm) and RuleLearner(r)



REGISTER NOW

*Alternative link:  
http://info.salford-systems.com/improve-your-regression

Can't make it? Sign up and receive the recording!



Abstract:

Join us for this two part webinar series on improving your regression using 
modern regression analysis techniques, presented by Senior Scientist, Mikhail 
Golovyna. In these webinars you will learn how to drastically improve 
predication accuracy in your regression with a new model that addresses common 
concerns such as missing values, interactions, and nonlinearities in your data.

We will demonstrate the techniques using real-world data sets and introduce the 
main concepts behind Leo Breiman's Random Forests and Jerome Friedman's GPS 
(Generalized PathSeeker(tm)), MARS(r) (Multivariate Adaptive Regression 
Splines), and Gradient Boosting.

[ECOLOG-L] job posting: Entry ­Level Marketing Statisti cian (San Diego, CA)

[Lisa Solomon]

Entry-Level Marketing Statistician

(San Diego, CA)


Salford Systems is an advanced data mining software and consulting company 
based in San Diego, California. We enjoy an open, creative environment, and 
have developed an international reputation for cutting-edge technology. Salford 
Systems is affiliated with several of the world's greatest scientists in the 
field of machine learning, and leads the data mining industry with exciting, 
innovative products.


The ideal candidate is passionate and enthusiastic about applied statistics and 
analytics. Qualified candidates should have strong ability to both engage with 
senior leaders to design well-constructed analyses and work with data 
scientists and software engineers to effectively deliver actionable results. 
They should have excellent communication skills and the ability to work with 
both technical and marketing departments to effectively create new educational 
materials, execute new promotional projects and actively contribute to 
consulting projects.


Responsibilities may include:


· Working with our technical and marketing departments to prepare data 
that will be used for promotional projects and consulting projects.

· Ability to prepare exemplary analyses on the prepared data to 
illustrate analytical techniques using our software.

· Scraping, merging, cleaning, formatting and repurposing of publicly 
available datasets.

· Ability to draw conclusions from data and recommend actions.

· Key participant in Marketing campaigns via creating 
easily-understood, step-by-step instructions.

· Understand and communicate product benefits.

· Perform hands-on competitive analysis.

· Add classical statistical approaches to data mining approaches to 
enhance our consulting projects.


Minimum Qualifications:

· Master’s Degree in statistics or related

· 2 years relevant experience including statistical software (R, 
S-Plus, SAS, or similar), databases and scripting languages (such as Python).


Preferred Qualifications:


· Marketing and/or writing background a plus.

· Experience using analytics and/or data mining software, such as 
Salford’s products, SAS, R, or similar products

· Real-world experience.

· Demonstrated willingness to both teach others and learn new 
techniques.

· Demonstrated self-direction.




Light travel required. Candidate should be legally authorized to work in the 
U.S.A.

Contact:

Please send resume and wage history and requirements to 
h...@salford-systems.com.


Company: Salford Systems
Location: San Diego, CA

Phone: 619-356-4156
Web: www.salford-systems.com

Careers: 
www.salford-systems-careers.com

[ECOLOG-L] Tomorrow: Webinar, 3 Ways to Improve your Regression with Data Science and Machine Learnging (no charge, part 2)

[Lisa Solomon]

Accept-Language: en-US
Content-Language: en-US
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acceptlanguage: en-US
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MIME-Version: 1.0

3 Ways to Improve your Regression with Data Science and Machine Learning Pa=
rt 2=20
=A0(no charge, Case Study, Step-by-step, Hands-on option)

Registration: http://hubs.ly/H01Y9Fr0
Alternative Link: http://info.salford-systems.com/3-ways-to-improve-your-re=
gression-part2

January 27th, 10AM - 11AM PT
* If the time is inconvenient, please register and we will send you a recor=
ding
* Part 1 is not required, to understand the approach and concepts in tomorr=
ow's webinar; but, if you want a refresher, you can see last week's webinar=
 at your convenience. =A0Link to recording of Part 1: http://hubs.ly/H01Q4b=
F0

ABSTRACT:  Last week, we showed you how you could drastically improve predi=
ction accuracy in your linear =A0regression with a new model that handles m=
issing values, interactions, AND nonlinearities in your data. =A0As a follo=
w-up to the last week's webinar, we will show you how to take data science =
techniques even further to extract actionable insight and take advantage of=
 advanced modeling features. You will walk away with several different meth=
ods to turn your ordinary regression into an extraordinary regression!

Techniques used:
*Stochastic gradient boosting: TreeNet plots show you the impact of every v=
ariable in your model; take it a step further by creating spline approximat=
ions to these variables and using them in a conventional linear regression =
for a boosted model performance!
* Nonlinear regression splines: MARS nonlinear regression will still give y=
ou what looks like a standard regression equation, but instead of coefficie=
nts, you'll see transformations of your original variables.
* Modeling automation: learn how to cycle through numerous modeling scenari=
os automatically to discover best-fit parameters.

Included with Registration:
* On-demand recording of webinar
* Data set used in presentation
* Step-by-step instructions
* 30-day free access to MARS, TreeNet, and Random Forests

More details:
* Last week, we showed you how you could drastically improve prediction acc=
uracy in your linear =A0regression with a new model that handles missing va=
lues, interactions, AND nonlinearities in your data. =A0This week, we will =
rebuild these original models and get straight to the more advanced feature=
s.=A0=20
* We will quickly review how to incorporate nonlinearities in a regression =
splines model=A0 AND THEN show you how to automatically detect interactions=
 and include these to lead to an even better result.
* We will quickly review stochastic gradient boosting, and how, with plots =
you can see how each variable contributes to your model.=A0=A0 And then, th=
is week you will see how to create approximations from these plots and use =
these in a standard linear regression as your inputs.
* We will also explore the benefits of model automation. Without any custom=
 programming, you can quickly cycle through different modeling scenarios, s=
uch as intelligently decreasing your predictor pool by removing variables o=
ne by one, or automatically re-running your regression model using differen=
t loss functions. This gives you the option to create many different models=
 and choose the best for your analysis needs.

These techniques are great for skeptics who like to stick with standard reg=
ression but wish to see dramatic improvements. With very large datasets, yo=
u will see a significant speed benefit as well.=A0 Learn what is being used=
 at some of the largest banks and credit companies in the world.

And if you want a refresher, you can see last week's webinar at your conven=
ience: http://hubs.ly/H01Q4bF0

Who should attend:=20
* Attend if you want to implement data science techniques even without a da=
ta science, programming, or even a statistical background.
* Attend if you want to understand why data science techniques are so impor=
tant for analysts.

Registration: http://hubs.ly/H01Y9Fr0
Alternative Link: http://info.salford-systems.com/3-ways-to-improve-your-re=
gression-part2

[ECOLOG-L] Webinar Series: 3 Ways to Improve your Regression (Hands-on Component)

[Lisa Solomon]

3 Ways to Improve your Regression (Case Study, Step-by-step, Hands-on option)


Registration: http://hubs.ly/H01Q4bF0

Alternative Link: 
http://info.salford-systems.com/3-ways-to-improve-your-regression-part1


January 20th and 27th, 10AM - 11AM PT
* If the time is inconvenient, please register and we will send you a recording.




ABSTRACT:
Linear regression plays a big part in the everyday life of a data analyst, but 
the results aren't always satisfactory. What if you could drastically improve 
prediction accuracy in your regression with a new model that handles missing 
values, interactions, AND nonlinearities in your data? Instead of proceeding 
with a mediocre analysis, join us for this 2-part webinar series.  We will show 
you how modern algorithms can take your regression model to the next level and 
expertly handle your modeling woes.  You will walk away with several different 
methods to turn your ordinary regression into an extraordinary regression!

This webinar will be a step-by-step presentation that you can repeat on your 
own!
Included with Registration:

* Webinar recording

* 30 day software evaluation

* Dataset used in presentation

* Step-by-step instruction for you to try at home

Who should attend:

* Attend if you want to implement data science techniques even without 
a data science, statistical or programming background.

* Attend if you want to understand why data science techniques are so 
important for forecasting.


Registration: http://hubs.ly/H01Q4bF0

Alternative Link: 
http://info.salford-systems.com/3-ways-to-improve-your-regression-part1



Part 1: January 20 - We introduce MARS nonlinear regression, TreeNet gradient 
boosting, and Random Forests and show you how to extract actionable insight. 
Techniques:

* Nonlinear regression splines (via MARS): this tool is ideal for users 
who prefer results in a form similar to traditional regression while allowing 
for bends, thresholds, and other departures from straight-line methods.

*  Stochastic gradient boosting (via TreeNet): this flexible and 
powerful data mining tool generates hundreds of decision trees in a sequential, 
error-correcting process to produce an extremely accurate model.

* Random Forests: this method combines many decision trees independent 
of each other and is best suited in analyses of small to moderate datasets.


Part 2: January 27 - We will show you how to take these techniques even further 
and take advantage of advanced modeling features.
**There will be overlap with Part 1. It is recommended to watch Part 1, but not 
required. Techniques:

* Stochastic gradient boosting: TreeNet plots show you the impact of 
every variable in your model; take it a step further by creating spline 
approximations to these variables and using them in a conventional linear 
regression for a boosted model performance!

* Nonlinear regression splines: MARS nonlinear regression will still 
give you what looks like a standard regression equation, but instead of 
coefficients, you'll see transformations of your original variables.

* Modeling automation: learn how to cycle through numerous modeling 
scenarios automatically to discover best-fit parameters.

[ECOLOG-L] tomorrow: Webinar: Tips & Tricks for Segmentation (Targeting/Profiling/Classification) with Data Science and Analytics

[Lisa Solomon]

Webinar: Tips & Tricks for Segmentation (Targeting/Profiling/Classification)

Registration: 
http://hubs.ly/y0Zfhr0
*Alternative link: 
http://info.salford-systems.com/customer-segmentation-webinar

July 21, 10AM - 11AM PDT
* If the time is inconvenient, please register and we will send you a recording.

Abstract:  Segmentation (Targeting, Profiling, Classification) is the process 
of dividing a database into distinct groups of individuals who share common 
characteristics.  This is readily accomplished using modern data mining and 
machine learning techniques. The methods are easily implemented and work well 
with large datasets containing nonlinearities, interactions in the data and a 
mix of categorical and numerical variables.

In this webinar, you will learn, via step-by-step instruction, how to use 
modern techniques to:

1)  segment a large database AND

2)  look at an already segmented/clustered database and discover the 
reasons for the class memberships.

We will demonstrate via an APPLIED example (Banking/Risk) and two additional 
case studies (Insurance/Renewals and HealthClub Membership/Insights).

Although we show three examples, the approach is widely applicable and you will 
be able to follow the same steps on your own datasets. Examples of datasets 
that would benefit include:

* Business: Marketing strategies, Targeted Sales , Fraud Detection

* Drug Discovery: Better Profiling including Adverse Events and 
Healthcare Outcomes

* Insurance Premium Optimization: finding variables, often 
non-intuitive,  providing clues into a prospect or customer's purchasing 
behavior and risk level

* Environmental: decision making for environmental management, 
population dynamics, habitat suitability

* Epidemiology: risk analysis, population dynamics

This webinar will be a step-by-step presentation that you can repeat on your 
own!
Included with Registration:

* Webinar recording

* 30 day software evaluation

* Dataset used in presentation

* Step-by-step instruction for you to try at home

Who should attend:

* Attend if you want to implement data science techniques even without 
a data science, statistical or programming background.

* Attend if you want to understand why data science techniques are so 
important for segmentation, including market segmentation, targeted marketing, 
multi-variable segmentation, etc.


Methods covered include:

* Decision Tree Techniques (CART)

* Boosting (Stochastic Gradient Boosting)

Registration: 
http://hubs.ly/y0Zfhr0
*Alternative link: 
http://info.salford-systems.com/customer-segmentation-webinar

[ECOLOG-L] Webinar: Tips & Tricks for Segmentation (Targeting/Profiling/Classification) with Data Science and Analytics

[Lisa Solomon]

Webinar: Tips & Tricks for Segmentation (Targeting/Profiling/Classification)

Registration: 
http://hubs.ly/y0Zfhr0
*Alternative link: 
http://info.salford-systems.com/customer-segmentation-webinar

July 21, 10AM - 11AM PDT
* If the time is inconvenient, please register and we will send you a recording.

Abstract:  Segmentation (Targeting, Profiling, Classification) is the process 
of dividing a database into distinct groups of individuals who share common 
characteristics.  This is readily accomplished using modern data mining and 
machine learning techniques. The methods are easily implemented and work well 
with large datasets containing nonlinearities, interactions in the data and a 
mix of categorical and numerical variables.

In this webinar, you will learn, via step-by-step instruction, how to use 
modern techniques to:

1)  segment a large database AND

2)  look at an already segmented/clustered database and discover the 
reasons for the class memberships.

We will demonstrate via an APPLIED example (Banking/Risk) and two additional 
case studies (Insurance/Renewals and HealthClub Membership/Insights).

Although we show three examples, the approach is widely applicable and you will 
be able to follow the same steps on your own datasets. Examples of datasets 
that would benefit include:

* Business: Marketing strategies, Targeted Sales , Fraud Detection

* Drug Discovery: Better Profiling including Adverse Events and 
Healthcare Outcomes

* Insurance Premium Optimization: finding variables, often 
non-intuitive,  providing clues into a prospect or customer's purchasing 
behavior and risk level

* Environmental: decision making for environmental management, 
population dynamics, habitat suitability

* Epidemiology: risk analysis, population dynamics

This webinar will be a step-by-step presentation that you can repeat on your 
own!
Included with Registration:

* Webinar recording

* 30 day software evaluation

* Dataset used in presentation

* Step-by-step instruction for you to try at home

Who should attend:

* Attend if you want to implement data science techniques even without 
a data science, statistical or programming background.

* Attend if you want to understand why data science techniques are so 
important for segmentation, including market segmentation, targeted marketing, 
multi-variable segmentation, etc.


Methods covered include:

* Decision Tree Techniques (CART)

* Boosting (Stochastic Gradient Boosting)

Registration: 
http://hubs.ly/y0Zfhr0
*Alternative link: 
http://info.salford-systems.com/customer-segmentation-webinar

[ECOLOG-L] Webinar: Tips & Tricks to Improve Your Logistic Regression

[Lisa Solomon]

Webinar: Tips & Tricks to Improve Your Logistic Regression
June 25, 10AM - 11AM PDT

* If the time is inconvenient, please register and we will send you a 
recording.

Registration Link: 
http://hubs.ly/y0T9ZQ0

* Alternative link: 
http://info.salford-systems.com/tips-and-tricks-for-logistic-regression

Abstract: Logistic regression is a commonly used tool to analyze binary 
classification problems. However, logistic regression still faces the 
limitations of detecting nonlinearities and interactions in data. In this 
webinar,
you will learn more advanced and intuitive machine learning techniques that 
improve on standard logistic  regression in accuracy and other aspects. As an 
APPLIED example, we will demonstrate using a banking dataset where we will  
predict future financial stress of a loan applicant in order to determine 
whether they should be granted  a loan. Although the focus is related to 
finance and loans, the concepts are relevant for anyone who actively uses 
logistic regression and wishes to improve accuracy and predictor understanding.

Logistic binary gradient boosting will be explained theoretically and shown in 
hands-on application
to generate accurate predicted probabilities.

This webinar will be a step-by-step presentation that you can repeat on your 
own!
Included with Registration:

* Webinar recording

* 30 day software evaluation

* Dataset used in presentation

* Step-by-step instruction for you to try at home

Registration Link: 
http://hubs.ly/y0T9ZQ0

* Alternative link: 
http://info.salford-systems.com/tips-and-tricks-for-logistic-regression

* If the time is inconvenient, please register and we will send you a 
recording.

[ECOLOG-L] Webinar: April 28th, Applied Example of Data Science Technology

[Lisa Solomon]

Webinar: Monday, April 28th
This webinar will be a step-by-step presentation that you can repeat on your 
own environmental AND APPLIED datasets! Although the focus is ROI and Business, 
corresponding Environmental Applications include: scenario planning, risk 
analysis, decision making for environmental management, population dynamics, 
habitat suitability and other environmental applications.

* If the time is inconvenient, please register and we will send you a 
recording.

Registration Link: 
http://hubs.ly/y0Jgh20
*Alternative link: 
http://info.salford-systems.com/maximizing-roi-webinar

Who should attend?  Attend if:

* You are interested in using data science technology for better 
modeling of your environmental datasets?

* You are curious about how data mining is used for forefront 
commercial and applied applications?

* You are able to see connections between forefront business 
applications and environmental applications.

Title: Webinar: Maximizing ROI (using State-of-the-Art Data Science Technology)

Abstract:  Return on investment (ROI) is a profitability measure that many 
companies use to quantify their efforts and make important business decisions. 
As an APPLIED example, we will look at ROI related to product sales and 
promotions at Walmart.  Although the focus is ROI and Business, corresponding 
Environmental Applications include: scenario planning, risk analysis, decision 
making for environmental management, population dynamics, habitat suitability 
and other environmental applications.   Using state-of-the-art data science 
techniques, and especially TreeNet gradient boosting, we will optimize product 
promotion options and maximize revenue and wider gain.

[ECOLOG-L] Webinar: 3 Ways to Improve your Regression

[Lisa Solomon]

Webinar: 3 Ways to Improve your Regression

Date/Time: February 10, 2015 from 10am-11am PDT

* If inconvenient time, please register and we will send you a 
recording.

Click to Register:
http://hubs.ly/y0tG8J0
OR
http://info.salford-systems.com/3-ways-to-improve-your-regression?utm_campaign=Regression&utm_source=EC

Abstract:

* Linear regression plays a big part in the everyday life of a data 
analyst, but the results are not always satisfactory. What if you could 
drastically improve prediction accuracy in your regression with a new model 
that handles missing values, interactions, AND nonlinearities in your data?

* Instead of proceeding with a mediocre analysis, join us for this 
presentation, which will show you how MARS non-linear regression, TreeNet 
gradient boosting, and Random Forests can take your regression model to the 
next level with modern algorithms designed to expertly handle your modeling 
woes.

* With these state-of-the-art techniques, you'll boost model 
performance without stumbling over confusing coefficients or problematic 
p-values!

Click to Register:
http://hubs.ly/y0tG8J0
OR
http://info.salford-systems.com/3-ways-to-improve-your-regression?utm_campaign=Regression&utm_source=EC

[ECOLOG-L] This Friday, NYC, Hands-on Data Mining Training, $35. Last-chance to Register

[Lisa Solomon]

Friday, August 22 in New York City
Hands-on Data Mining Training, only $35.

Click to Register: 
http://hub.am/1w67LBN<https://app.getsignals.com/link?url=http%3a%2f%2fhub.am%2f1w67LBN&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=997710aa559f408db31d87e98f75084c>

Or click here to suggest other locations:
http://hubs.ly/y01L9D0<https://app.getsignals.com/link?url=http%3a%2f%2fhubs.ly%2fy01L9D0&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=7b18e4a748894f3cb48d66d5cd447ee7>

Cost: $35 (includes free 90-day access to the SPM Salford Predictive Modeler 
technology)

Agenda
Data Mining Quickstart

 *   8:30am-9:00am - Breakfast/Check-in
 *   9:00am-12:00pm -- Introduction to Data Mining and Case Study Examples
 *   12:00pm-1:00pm -- Lunch (provided)
Hands-On Technical Session (Bring your own laptop)
1:00pm-3:00pm

 *   Build and Score Predictive Models
 *   Optimization for Predictive Accuracy
 *   Create Reports: Translating insights into actionable results
Why you should attend:

 *   Get step-by-step instruction for the most popular data mining techniques 
used in predictive analytics including decision trees, classification, 
segmentation, non-linear regression, ensemble methods, boosted decision trees, 
etc.
 *   Walk away with everything you will need to start your own data mining 
projects.
 *   Be ready to apply your new data mining knowledge at your organization to 
create immediate value.
 *   All attendees receive 90-day access to the SPM Salford Predictive Modeler 
technology.
Salford Systems' Training Seminars offer crystal clear instruction and a wealth 
of real-world consulting experience. This seminar will provide a great 
opportunity to use data mining technology and to understand how to apply data 
mining to your business and/or research needs.

Questions?
Please contact Lisa Solomon 
li...@salford-systems.com<mailto:li...@salford-systems.com>

[ECOLOG-L] Chicago, Data Mining Training (Hands-On, $35), Chicago, May 23rd

[Lisa Solomon]

Join us for a hands-on data mining training in Chicago, IL on May 23, 2014:

* Cost: $35

* Registration: 
http://hub.am/1mecIVh

Agenda:

8:30am-9:00am Breakfast (provided)

* 9:00am-12:00pm

* Introduction to Data Mining

* Case Study Examples
12:00pm-1:00pm Lunch (provided)

* 1:00pm-3:00pm

* Build and Score Predictive Models

* Optimization for Predictive Accuracy

* Create Reports: Translating insights into actionable results

Why you should attend:

* Get step-by-step instruction for the most popular data mining 
techniques used in predictive analytics including decision trees, 
classification, segmentation, non-linear regression, ensemble methods, boosted 
decision trees, etc.

* Walk away with everything you will need to start your own data mining 
projects.

* Be ready to apply your new data mining knowledge at your organization 
to create immediate value.

* All attendees receive 90-day access to the SPM Salford Predictive 
Modeler technology.

We hope to see you in Chicago!

[ECOLOG-L] San Diego, CA, Data Mining Training (Hands-On, $35), San Diego, April 25th

[Lisa Solomon]

Subject: Data Mining Training (Hands-On, $35), San Diego, April 25th

More information: 
http://hub.am/1pO5Kc1<https://app.getsignals.com/link?url=http%3a%2f%2fhub.am%2f1pO5Kc1&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=13494d5c5ec548af99b99167c78d6f6e>
Cost: $35 (includes free 90-day access to the SPM Salford Predictive Modeler 
technology)
Agenda

Data Mining Quickstart

 *   9:30am-10:00am -- Breakfast
 *   10:00am-11:00am -- Introduction to Data Mining
 *   11:00am-12:00pm -- Case Study Examples
 *   12:00pm-1:00pm -- Lunch (provided)

Hands-On Technical Session (Bring your own laptop)

 *   1:00pm-4:00pm
*   Build and Score Predictive Models
*   Optimization for Predictive Accuracy
*   Create Reports: Translating insights into actionable results


Why you should attend:

 *   Get step-by-step instruction for the most popular data mining techniques 
used in predictive analytics including decision trees, classification, 
segmentation, non-linear regression, ensemble methods, boosted decision trees, 
etc.
 *   Walk away with everything you will need to start your own data mining 
projects.
 *   Be ready to apply your new data mining knowledge at your organization to 
create immediate value.
 *   All attendees receive 90-day access to the SPM Salford Predictive Modeler 
technology.

* Salford Systems' Training Seminars offer crystal clear instruction 
and a wealth of real-world consulting experience. This seminar will provide a 
great opportunity to use data mining technology and to understand how to apply 
data mining to your business and/or research needs.

San Diego Location: San Diego Training and Conference Center, 350 Tenth Ave., 
Suite 950, San Diego, CA 92101

Please contact me if you should have any questions.

Sincerely,
Lisa Solomon

li...@salford-systems.com<mailto:li...@salford-systems.com>

(619) 543-8880 x109

www.salford-systems.com<https://app.getsignals.com/link?url=http%3a%2f%2fwww.salford-systems.com&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=378e13a21c5e4e25ab43add91a05a332>

[ECOLOG-L] Data Mining Training (Hands-On, $35), Washington DC, San Diego and other locations

[Lisa Solomon]

Hands-on Data Mining Training
Friday, April 4th in Washington DC
Friday, April 25 in San Diego

Registration: 
http://hub.am/N4tlqg<https://app.getsignals.com/link?url=http%3a%2f%2fhub.am%2fN4tlqg&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=89afabaa104044399e0402a02a7a7a8d>
*for Washington DC and San Diego

Other Locations: 
http://hub.am/1cViLyw<https://app.getsignals.com/link?url=http%3a%2f%2fhub.am%2f1cViLyw&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=5f2acc003ea049fea48110df9b57659f>
Interested in Other Locations?   Use the above link to tell us where.
*We've already planned for May in Chicago; June in Houston; and, we will soon 
schedule Silicon Valley, Anaheim, and online.
Cost: $35 (includes free 90-day access to the SPM Salford Predictive Modeler 
technology)
Agenda

Data Mining Quickstart

 *   9:30am-10:00am -- Breakfast
 *   10:00am-11:00am -- Introduction to Data Mining
 *   11:00am-12:00pm -- Case Study Examples
 *   12:00pm-1:00pm -- Lunch (provided)

Hands-On Technical Session (Bring your own laptop)

 *   1:00pm-4:00pm
*   Build and Score Predictive Models
*   Optimization for Predictive Accuracy
*   Create Reports: Translating insights into actionable results


Why you should attend:

 *   Get step-by-step instruction for the most popular data mining techniques 
used in predictive analytics including decision trees, classification, 
segmentation, non-linear regression, ensemble methods, boosted decision trees, 
etc.
 *   Walk away with everything you will need to start your own data mining 
projects.
 *   Be ready to apply your new data mining knowledge at your organization to 
create immediate value.
 *   All attendees receive 90-day access to the SPM Salford Predictive Modeler 
technology.

* Salford Systems' Training Seminars offer crystal clear instruction 
and a wealth of real-world consulting experience. This seminar will provide a 
great opportunity to use data mining technology and to understand how to apply 
data mining to your business and/or research needs.

Washington DC Location: The American Institute of Architects, 1735 New York 
Avenue, NW, Washington, DC 20006
San Diego Location: San Diego Training and Conference Center, 350 Tenth Ave., 
Suite 950, San Diego, CA 92101

Please contact me if you should have any questions.

Sincerely,
Lisa Solomon

www.salford-systems.com<https://app.getsignals.com/link?url=http%3a%2f%2fwww.salford-systems.com&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=378e13a21c5e4e25ab43add91a05a332>

[ECOLOG-L] Data Mining Training (Hands-On), New York City and other locations

[Lisa Solomon]

Hands-on Data Mining Training
Friday, March 28 in New York City
*or request other dates/locations including Silicon Valley, Washington DC, 
Houston, Anaheim, Chicago, online

Location:
Manhattan GMAT Center Location
138 West 25th St. (b/w 6th & 7th Ave)
New York, NY 10001
Click to Register(or suggest other locations): 
http://hub.am/NbWhwX<https://app.getsignals.com/link?url=http%3a%2f%2fhub.am%2fNbWhwX&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=6317b4d4828141a9a79ce67282df6d3a>
Cost: $35 (includes free 90-day access to the SPM Salford Predictive Modeler 
technology)


Agenda

Data Mining Quickstart

 *   9:30am-10:00am -- Breakfast
 *   10:00am-11:00am -- Introduction to Data Mining
 *   11:00am-12:00pm -- Case Study Examples
 *   12:00pm-1:00pm -- Lunch (provided)

Hands-On Technical Session (Bring your own laptop)

 *   1:00pm-4:00pm
*   Build and Score Predictive Models
*   Optimization for Predictive Accuracy
*   Create Reports: Translating insights into actionable results


Why you should attend:

 *   Get step-by-step instruction for the most popular data mining techniques 
used in predictive analytics including decision trees, classification, 
segmentation, non-linear regression, ensemble methods, boosted decision trees, 
etc.
 *   Walk away with everything you will need to start your own data mining 
projects.
 *   Be ready to apply your new data mining knowledge at your organization to 
create immediate value.
 *   All attendees receive 90-day access to the SPM Salford Predictive Modeler 
technology.

* Salford Systems' Training Seminars offer crystal clear instruction 
and a wealth of real-world consulting experience. This seminar will provide a 
great opportunity to use data mining technology and to understand how to apply 
data mining to your business and/or research needs.

Please contact me if you should have any questions.

Sincerely,
Lisa Solomon

www.salford-systems.com<https://app.getsignals.com/link?url=http%3a%2f%2fwww.salford-systems.com&ukey=agxzfnNpZ25hbHNjcnhyGAsSC1VzZXJQcm9maWxlGICAgMCxqZwIDA&k=378e13a21c5e4e25ab43add91a05a332>

[ECOLOG-L] Webinar: Advances in Regression: Modern Ensemble and Data Mining Approaches (hands-on, no charge)

[Lisa Solomon]

Hands-on Webinar (no charge)
Advances in Regression: Modern Ensemble and Data Mining Approaches
**Part of the series: The Evolution of Regression from Classical Linear 
Regression to Modern Ensembles

Register Now for Parts 3, 4:  https://www1.gotomeeting.com/register/500959705
**All registrants will automatically receive access to recordings of Parts 1 & 
2.

Course Abstract: Overcoming Linear Regression Limitations
 Regression is one of the most popular modeling methods, but the classical 
approach has significant problems. This webinar series addresses these 
problems. Are you working with larger datasets? Is your data challenging? Does 
your data include missing values, nonlinear relationships, local patterns and 
interactions? This webinar series is for you!
 In our March 29th session (Part 3), we will focus on modern ensemble and 
data mining approaches. These methods dramatically improve the performance of 
weak learners such as regression trees. The techniques discussed here enhance 
the performance of regression trees considerably. These methods inherit the 
good features of trees (variable selection, missing data, mixed predictors) and 
improve on the weak features such as prediction performance.
 Did you miss parts 1 and 2? With your registration, you will receive links 
to the recordings of Part 1 and 2. Covered in part 1 and 2 are  improvements to 
conventional and logistic regression, as well as a discussion of classical, 
regularized, and nonlinear regression from both a theoretical and hands-on 
point of view. The hands-on component includes a step-by-step demonstration 
with instructions for reproducing the demo at your leisure. Especially for the 
dedicated student: after watching this recording, you will be able to apply 
these methods to your own data.

Part 3: March 29, 10-11am PST - Regression methods discussed:

* Nonlinear Ensemble Approaches:

o   TreeNet Gradient Boosting

o   Random Forests

o   Gradient Boosting incorporating Random Forests

* Ensemble Post-Processing:

o   ISLE Importance Sampled Learning Ensembles

o   RuleLearner rule based learning ensembles

Part 4: April 12, 10-11am PST - Hands-on demonstration of concepts discussed in 
Part 3

 *   Step-by-step demonstration
 *   Datasets and software available for download
 *   Instructions for reproducing demo at your leisure
 *   For the dedicated student: apply these methods to your own data (optional)

[ECOLOG-L] Early-Bird Deadline, Schedule: Data Mining Conference in California - Salford Systems

[Lisa Solomon]

Salford Data Mining Conference
August 23rd - 25th, 2009
San Diego, California

Early-Bird Registration Deadline: July 24th, 2009

http://SalfordDataMining.com/agenda.php

Post-Conference Training
August 26th - 28th, 2009

Especially of interests to environmentalists:

   * Fusing Information Content of Data-Driven and Theoretical-Based Models, 
Case Study: Unexploded Ordinance Discrimination
   * "Combining Linear and Non-Linear Modeling Techniques: Getting the Best of 
Two Worlds
   * Case Study Presentations illustrating the use of RandomForests
   * Environmental Predictive Modeling: Presentation from the International 
Arctic Research Center using TreeNet:

Predictive Modeling   of Dimethylsulfide(DMS)in the Global Ocean

Other conference topics include:

   * What Data Mining Has to Say About the Financial Crisis
   * Maximizing Profit of High Volume Direct Marketing Campaigns
   * Interaction Detection and Financial Market Behavior
   * Predicting Healthcare Costs and Risk-Adjusting Healthcare Cost Predictions
   * Data Mining Approaches to Modeling Insurance Risk
   * Disease Prediction
   * Clinical Data Analysis
   * Actuarial and Underwriting Analytics
   * Interaction Detection for Discovery of Disease Causing Genetics
   * Online Advertising
   * Fraud Detection
   * Defense: Modeling Terrorism, Detecting Complex Attacks
   * Mini-Tutorial: Combining Linear and Non-Linear Modeling Techniques
   * Presentations by Developers of CART, MARS, TreeNet and Random Forests
   * And Many More

Attendees at prior conferences included: The International Monetary Fund, 
Barnes and Noble, Pfizer, Union Bank, Wells Fargo, Stanford Linear Accelerator 
Center, Cold Spring Harbor Laboratory, Novartis, Columbia University School of 
Public Health, Harvard Medical School, HSBC, International Steel Group, Cap 
Gemini, AT&T Labs-Research, PricewaterhouseCoopers, and Liberty Mutual 
Insurance.

The 2009 Salford Data Mining Conference is aimed at bringing together 
researchers and practitioners to learn about data mining technology from 
practical and theoretical experts. This venue will serve as a place to learn 
data mining technology and anticipated future developments from industry 
leading experts. It will also allow attendees to exchange ideas and experiences 
focused on the practice of data mining and the art and practice of real world 
analysis of complex data.

We look forward to seeing you at the 2009 Salford Data Mining Conference.

Please visit our website at http://SalfordDataMining.com/agenda.php for the 
latest information.

Free Webinar: Vendor Neutral Intro to Data Mining for Absolute Beginners, May 23, 2007

[Lisa Solomon]

ONLINE VENDOR NEUTRAL INTRO TO DATA MINING FOR ABSOLUTE BEGINNERS
(no charge)

A non-technical data mining introduction for absolute beginners
May 23, 2007, 10AM - 11AM PST
Future Sessions (June 14, Sept 7)

To register for the webinar 
--- 
1. Go to https://salford.webex.com/salford/onstage/g.php?d=928318845&t=a 
2. Click "Enroll". 
3. On the registration form, enter your information and then click "Submit".

Once you have registered, you will receive a confirmation email message with 
instructions on how to join the event, as well as audio and system 
requirements.  Please read this confirmation email carefully!

This one-hour webinar is a perfect place to start if you are new to data mining 
and have little-to-no background in statistics or machine learning. 

In one hour, we will discuss:

**Data basics: what kind of data is required for data mining and predictive 
analytics; In what format must the data be; what steps are necessary to prepare 
data appropriately 

**What kinds of questions can we answer with data mining

**How data mining models work: the inputs, the outputs, and the nature of the 
predictive mechanism 

**Evaluation criteria: how predictive models can be assessed and their value 
measured 

**Specific background knowledge to prepare you to begin a data mining project.

Please do not hesitate to contact me if you have any questions.

Sincerely,
Lisa Solomon
[EMAIL PROTECTED]

Free Webinar: Vendor Neutral Intro to Data Mining for Absolute Beginners, January 26, 2007

[Lisa Solomon]

ONLINE VENDOR NEUTRAL INTRO TO DATA MINING FOR ABSOLUTE BEGINNERS
(no charge)

A non-technical data mining introduction for absolute beginners
January 26, 2007, 10AM - 11AM PST
Future Sessions (May 23, June 14, Sept 7)
To register: contact [EMAIL PROTECTED]

This one-hour webinar is a perfect place to start if you are new to data mining 
and have little-to-no background in statistics or machine learning. 

In one hour, we will discuss:

**Data basics: what kind of data is required for data mining and predictive 
analytics; In what format must the data be; what steps are necessary to prepare 
data appropriately 

**What kinds of questions can we answer with data mining

**How data mining models work: the inputs, the outputs, and the nature of the 
predictive mechanism 

**Evaluation criteria: how predictive models can be assessed and their value 
measured 

**Specific background knowledge to prepare you to begin a data mining project.

Please do not hesitate to contact me if you have any questions or if you wish 
to register.

Sincerely,
Lisa Solomon
[EMAIL PROTECTED]

Data Mining Events in August: Seattle, San Diego, Philadelphia

[Lisa Solomon]

DATA MINING TRAININGS, ONSITE VISITS, DEMONSTRATIONS

ONSITE VISITS/DEMONSTRATIONS
Locations: PHILADELPHIA, SEATTLE and SAN DIEGO
Dates: August 10-11 (Seattle), August 14-18 (San Diego), August 24-25 
(Philadelphia)

Dr. Dan Steinberg, CEO of Salford Systems, will be visiting Seattle, San Diego 
and Philadelphia in August.  If you and your colleagues would like to arrange a 
meeting time at your offices, please let us know as soon as possible.  Dr. 
Steinberg can discuss your specific application and how these would benefit 
from predictive modeling and data mining.  In demonstating the power of data 
mining and our tools, he can, if you wish, use your data. See more information 
regarding Salford Systems at the bottom of this email.

**
DATA MINING TRAINING
Locations: PHILADELPHIA and SEATTLE
Dates: August 9 (Seattle) and August 14, 15, 16, 17, 18 (Philadelphia)

SEATTLE DATA MINING TRAINING
Sponsored by the American Statistical Association 
Wednesday, August 9th
Computer Technology Workshops: CE_34T, CE_37T, CE_40T
http://www.amstat.org/meetings/jsm/2006/index.cfm?fuseaction=registration

PHILADELPHIA HANDS-ON DATA MINING TRAINING
August 14-18, 2006
Register for 1, 2, 3, 4 or 5 days.
http://www.salford-systems.com/servicestraining.php

Please let me know if I can help you with any of the above.
Best regards,
Lisa Solomon
Ph: (619)543-8880
Email: [EMAIL PROTECTED]

More information about Salford Systems Data Mining Tools:

Salford Systems has focused its efforts on becoming best of breed in the 
specific areas of decision, trees, boosted decision trees, spline regression 
(MARS) and tree ensembles (bagging, arcing, random forests).  Our tools are 
based on the original code of the creators of the proprietary CART algorithm.  
CART's creators continue to collaborate with Salford Systems to refine CART and 
to develop the next generation of data-mining tools.   We have extended the 
original code in collaboration with Jerome Friedman and Leo Breiman to include 
innovative features not found elsewhere, including patent pending extensions. 
We have exclusive access to the proprietary source code written by Jerome 
Friedman for CART, TreeNet, MARS, PRIM, and will be adding further Friedman 
tools in 2007.

* Robustness: Our software is known for its capability of handling large 
problems, and of running problem free no matter how complex the sequence of 
analytical steps required in a user session.
 

* Our latest versions include modeling automation to radically accelerate model 
development. In a recent client visit one of our senior scientists was able to 
build a response model in one day that significantly outperformed the client's 
model that had been hand crafted over 3 months. The built-in modeling 
automation allowed him to find that model in hours.

* Ease of use: Our unique visual displays make it easy for users to understand 
the data and quickly move to effective models. It is possible to start building 
a model in as few as 3 mouse clicks (open a data source, select a target 
variable, go).

* Analytical power: Our tools have now been used to win 14 data mining "medals" 
since 2000.

* Availability on multiple platforms

* Command-line support allows automated runs.

Early-Bird Deadline Extension till May 3rd for SYDNEY, AUSTRALIA Data Mining Training and Workshop

[Lisa Solomon]

Register by May 3rd to take advantage of our 20% early-bird discount!
http://www.salforddatamining.com/docs/regform06sydney.pdf

Data Mining Training and Workshop
Sponsored by the Institute of Analytics Professionals of Australia and Salford 
Systems

Training: June 5-7, 2006
Workshop: June 8, 2006

Location:
Australian Graduate School of Management Lecture Theatre
Number 1 O'Connell Street
Sydney, Australia

Objective: The training and workshop are aimed at bringing together
researchers and practitioners to learn about data mining technology from
practical and theoretical experts.  Expect to exchange ideas and
experiences focused on the practice of both data mining and the real
world analysis of complex data.

REAL-WORLD CASE STUDY PRESENTATIONS: Business, Biomedical and Operations 
Research Applications
See Program details below.

TRAINING and MODELLING STRATEGIES
See Details below.

To be added to the conference mailing list, please register your
interest at: http://www.salforddatamining.com/2006InfoRequest.php
Alternatively, respond to this email with the Subject: SYDNEY.

**
PROGRAM

BANKING:
Andrew Cathie, GE Money
"Application Score Card Development for a Consumer Finance Product"

Rita Chakravarti, Citibank, N.A.
"Bureau Policy Development and Better Targeting in Consumer Business
Using CART"

EPIDEMIOLOGY and PUBLIC HEALTH:
Dr. Shenghan Lai, Johns Hopkins University Medical School
"MARS, CART, TreeNet/MART for Epidemiological Research: Identifying
Relationships That Cannot Be Identified In Any Other Way"

Dean McKenzie, Department of Epidemiology and Preventive Medicine, 
Monash University
"Hazardous or Harmful Alcohol Use in Royal Australian Navy
Veterans of the 1991 Gulf War: Identification
of High Risk Subgroups"

INSURANCE/ACTUARIAL:
Inna Kolyshkina, Price Waterhouse Coopers
"Text Mining in the Insurance Industry"

Richard Brookes, Taylor Fry Consulting Actuaries and Mitchell Prevett,
Price Waterhouse Coopers
"Statistical Case Estimation Modelling - An Overview of the NSW
WorkCover Model"

Charles Pollack, Suncorp Metway Actuarial Services
"Experiences Applying Insurance Tasks to the New CART 6 Software:
Customer Retention and Data Analytics"

LOGISTICS and OPERATIONS RESEARCH
Bradley Utz, Schneider National, Inc.
"Using Classification Trees to Explain Failure to Deliver On-Time"

MARKET RESEARCH and CRM:
David McCloskey, Pathfinder Solutions
"Achieving Better Insights Into Customer Behaviour Through Integrating
Market Research with Decision Tree Behaviour Modelling"

MICROARRAY:
Svetlana Shchegrova, Agilent Technologies
"Microarrays: Training Microarrays to Measure DNA Copy Number"

TELECOMMUNICATIONS:
Inna Kolyshkina, Price Waterhouse Coopers
"Text Mining in the Telecommunications Industry"

**
TRAINING and MODELLING STRATEGIES
"Tutorials Introducing CART , MARS, TreeNet, MART and RandomForests"

"New Features in CART and TreeNet"

"Creative Use of Data Mining to Win Two Top Data Mining Competitions"

**
Please feel free to forward this email to any colleagues who might be
interested in attending.

Best regards,
Lisa Solomon
Salford Systems
Phone: 001-619-543-8880
Fax: 001-619-543-
E-mail: [EMAIL PROTECTED]
Website: www.salforddatamining.com

Environmental/Biostatistical Track, Schedule and Highlights, San Diego Data Mining Conference, March 29-31, San Diego, California

[Lisa Solomon]

Subject: Environmental/Biostatistical Track, Schedule and Highlights, 
San Diego Data Mining Conference, March 29-31, San Diego, California
* Conference begins at 6PM on March 29th.

Focusing on the Contributions of Data Mining to Solving Real World 
Challenges

2 Full Days of Case Study Presentations on March 30th and 31st.  
Conference begins at 6PM on March 29th with a Welcome Reception.
 
CONFERENCE SCHEDULE
<http://www.salforddatamining.com/program.htm>http://www.salforddatamining.com/docs/schedule06.pdf
 


ENVIRONMENTAL AND BIOSTATISTICAL TRACKS including presentations related 
to Biodiversity Modeling, Bird Flu, Spatial-GIS Data, Near Infrared 
Spectroscopy, Drug Discovery, Clinical Medicine, Microarrary Data 
Analysis, Drug Safety and Epidemiology

MINI-TUTORIALS and PRESENTATIONS
2 mini-tutorials and 13 presentations related to data mining as it 
applies to biostatistical and bioinformatics modeling.  Please see the 
detailed list of topics and presenters below.
 
PRE-CONFERENCE HANDS-ON TRAINING
March 27 - March 29, 2006
 
Network with Data Mining Experts and Pick up Pointers from 
Biostatistical Professionals and also from statistically-minded 
professionals in non-medical industries using techniques that might also 
be of interest in Biostatistics.

Registration: http://www.salforddatamining.com/registration.htm

If you have an interest in attending this conference or the 
pre-conference training, please contact Lisa Solomon:
Phone: 619-543-8880 x109, Email:  [EMAIL PROTECTED] 
<mailto:[EMAIL PROTECTED]>
- 

Detailed Information:
 
TUTORIALS:
 
Random Forests Tutorial: Case Study Examples from Autism, Multiple 
Schlerosis and Microarray Data
Presenter: Adele Cutler, Co-Developer of Random Forests.
 
"Overcoming Obstacles of Publishing in Medical Journals:
Explaining the Value of Data Mining to a Resistant Audience"
Presenter: Marsha Wilcox, I3 Drug Safety, Harvard Medical School and 
Boston University
 
BIOSTATISTICALLY-ORIENTED PRESENTATIONS:
 
Keynote: Application of Novel Tree-Based Methods to Modeling the 
Genetics of Complex Disease, Finding Genotypes and Various Interactions"
Presenter: Dr. Richard Olshen, Stanford University Medical School
 
"Bird Flu, Investigations and Spatial Modeling of Bird Flu in Alaska, 
Russian Far East and Elsewhere: Applications of the Salford Systems 
Software Suite Along International Flyways"
Presenter: Dr. Falk Huettmann, University of Alaska, Centre for Wildlife 
Ecology
 
"Classification of the Near Infrared Spectrum by TreeNet. Case Study 
Related to Food Eaten in East Asia and Japan"
Presenter: Dr. Mikio Kahara, Ichinoseki National College of Technology, 
Japan
 
"Automatized Methods For Finding the Best Algorithm Setting for Modeling 
Biodiversity Data in a Spatial GIS-Setting: MARS (Multivariate Adaptive 
Regression Splines) and Beyond"
Presenter: Dr. Falk Huettmann, University of Alaska, Centre for Wildlife 
Ecology
"MARS, CART, TreeNet/MART for Epidemiological Research: Identifying 
Relationships That Cannot Be Identified In Any Other Way"
Presenter: Dr. Shenghan Lai, Johns Hopkins University Medical School
 
"Combining CART, MARS, TreeNET, Neural Networks and Genetic 
Algorithm/Support Vector-Like Machines for Drug Discovery: The Search 
for Orally Effective, Non-Toxic Integrase Inhibitors for the Treatment 
and Possible Prevention of HIV Infection"
Presenter: Dr. Wayne Danter, Critical Outcomes Technologies
 
"Developing Predictive Models, a Comparison of Standard Regression
and Data Mining Methods: Case Studies Related to Obesity and In-hospital
Mortality, A Comparison of Data Mining Methods versus Standard
Regression Techniques (MARS vs OLS)"
Presenter: Dr. Paul Kolm, Emory University Medical School
 
"Umbilical Cord Length, Other Placental Growth Measures, Placental 
Weight and Birthweight"
Presenter: Dr. Carrie Salafia, Columbia University School of Public Health
 
"Classification and Regression Tree (CART) Analysis to Identify
Patients at Low-Risk for Injury Following Trauma"
Presenter: Dr. Jason Haukoos, Denver Health Medical Center
 
"Multi-level Hybrid CART-logit Models to Predict Early Childhood Caries 
with Individual, Family and Neighborhood Factors"
Presenter: Dr. Stuart Gansky, University of California San Francisco 
Dental School
 
"Drug Safety in ADHD"
Presenter: Dr. Marsha Wilcox, I3 Drug Safety and Harvard Medical School 
and Boston University Medical School
 
"Tissue Microarray Data: Random Forest Clustering.  A Focus on the Use 
of Random Forest Dissimilarities for Tumor Class Discovery and the 
Theoretical Properties of a Random Forest Dissimilarity"
Presenter: Dr. Steve Horvath, University of California, Los Angeles
 
"A Feature Selection Algorithm with Redundant Expressed Gene Filtering
from Microarray D

March 29-31, Full Environmental Track at Data Mining Conference, Southern California, Early-bird Deadline Savings of $50

[Lisa Solomon]

SALFORD SYSTEMS DATA MINING CONFERENCE 2006
San Diego, California, March 29-31, 2006
Focusing on the Contributions of Data Mining to Solving Real-World 
Challenges

Environmental, Biomedical and Business Real-World Case Study Presentations

ENVIRONMENTAL PRESENTATIONS INCLUDE:
"Investigations and Spatial Modeling of Bird Flu"
"Infrared Reflectance Spectroscopy for Assessment of Soil Properties"
"Automatized Methods for Finding the Best Algorithm Setting for Modeling 
Biodiversity Data in a Spatial GIS-Setting"

THE FOLLOWING ENVIRONMENTAL PRESENTATIONS FROM OUR 2004 and 2005 
CONFERENCES ARE AVAILABLE AT NO CHARGE
"Evolution of High-Diversity Areas in Ecuador in the Context of Global 
Climate Change"
"Experiences when applying MARS and CART in the Disciplines of 
Biodiversity, Conservation and Wildlife Modeling: The GIS Link"
"The Importance of CART and MARS in Environmental Fate and Risk 
Assessment for Pesticides"
"Atmospheric Pollution Forecasting"/
/"Applications for Wildlife Research and Conservation Management: An 
overview linking CART and MARS with GIS"

LEARN ABOUT DATA MINING:
You will learn about how the same techniques used by major credit 
companies for detecting fraudulent activity and by pharmaceutical 
companies for drug discovery can be used in environmental modeling. 
Examples will be shown where standard statistical methods were less 
accurate in developing a prediction model.  Business and Biomedical 
Topics Include:
Credit Risk Modeling; Targeted Marketing and Campaign Optimization; New 
Methods for Personalization; Analytical CRM; Fraud Detection; Drug 
Discovery; Data Analysis Related to Insurance, Epidemiology, Clinical 
Medicine, Proteomics and Genomics, Mass Spectrometry and Demographic 
Data; Tools for "Tall and Wide" Data

State-of-the-Art Research from Leading Academic Institutions

**A Commemoration and Celebration of the Lifetime Achievements of Data 
Mining Visionary and World-Renowned Statistician Leo Breiman

PRE-CONFERENCE TRAINING
Sharpen your expertise!
In-depth courses available for attendees who are new to data mining.

REGISTER NOW!  EARLY-BIRD DEADLINE SAVINGS OF $50
http://www.salforddatamining.com/docs/regform06.pdf

CONFERENCE PROGRAM:
http://www.salforddatamining.com/program-sd.htm

GREAT NETWORKING OPPORTUNITY
Attendees at Prior Conferences Included:
Real Jardin Botanico, Institute of Arctic Biology of University of 
Alaska-Fairbanks,  Syngenta Crop. Protection, ICF Consulting/Systems 
Applications International, Inc., The International Monetary Fund, 
Barnes and Noble, Pfizer, Union Bank, Wells Fargo, Ciphergen, Stanford 
Linear Accelerator, Johns Hopkins Medical School, UC Berkeley, Cold 
Spring Harbor Laboratory, Novartis, Columbia University School of Public 
Health, Harvard Medical School, HSBC, International Steel 
Group(Bethlehem Steel), Cap Gemini, AT&T Labs-Research, 
PricewaterhouseCoopers

Sincerely,
Lisa Solomon