y own. GridsearchCV give me just one pool of params, if they are
overfitting, i cant use gridsearchCV? Just having problems to understand
this.
On 12 May 2016 at 13:45, Olivier Grisel wrote:
> 2016-05-12 13:02 GMT+02:00 A neuman :
> > Thanks for the answer!
> >
> > but h
Thanks for the answer!
but how should i check that its overfitted or not?
best,
--
Mobile security can be enabling, not merely restricting. Employees who
bring their own devices (BYOD) to work are irked by the imposition
Hello everyone,
I'm having a bit trouble with the parameters that I've got from
gridsearchCV.
For example:
If i'm using the parameter what i've got from grid seardh CV for example on
RF oder k-nn and i test the model on the train set, i get everytime an AUC
value abo
The custom metric, ist just calculating the tanimoto coef.
a=x.tolist()
b=y.tolist()
c=np.count_nonzero(x==y)
a1=a.count(1.0)
b1=b.count(1.0)
return float(c)/(a1 + b1 - c)
so im Just counting 1's in x and 1's in y
c= are the numer, where 1's are matc
. 0. 0. 1. 0. 0. 0. 0.
0. 0. 0. 0. 0. 1. 0. 0. 1. 0. 1. 0. 0. 1. 0. 1. 1. 0.
1. 1. 1. 1. 0.]
and so on..
but X should be also containing 1's and 0's.
best,
On 12 January 2016 at 19:04, A neuman wrote:
> Hey,
>
> I Have an another problem,
>
Hey,
I Have an another problem,
if I'm using my own metric, there are not only the samples in x and y.
I'm using a 10 fold cv with k-NN Classifier.
My Attributes are only 1's and 0's, but if im printing them out, I'll get:
KNeighborsClassifier(metric=myFunc)
def myFu
Ah, that helped me a lot!!!
So i just write my own function that returns an skalar. This function is
used in the metric parameter of the kNN function.
Thank you!!!
On 9 January 2016 at 03:41, Sebastian Raschka wrote:
> You could just need “regular" Python function that outputs a sca
Hello everyone,
I actually want to use the KNeighboursClassifier, with my own distances.
in the Documentation stands the following:
[callable] : a user-defined function which accepts an array of distances,
and returns an array of the same shape containing the weights.
I just dont know, how
Hi
I was interested in the implementation of *stacking ensemble
meta-estimator*for the scikit-learn project, and as suggested by a
previous email on the
mailing list I've gone through the source-code of scikit-learn in general
and the source code of ensemble methods in specific.
I want to
>>We are still missing a stacking ensemble meta-estimator:
>>http://www.machine-learning.martinsewell.com/ensembles/stacking/Wolpert1992.pdf<http://www.machine-learning.martinsewell.com/ensembles/stacking/Wolpert1992.pdf>
>> (2748
citations)
I would be glad to work on thi
>> Do you believe that it is a major tool that is very useful in general?
I'm not sure it's the best option, but the main motive I had behind sending
this is my desire to add new features to the ensemble package of
scikit-learn
>> Have you had a lot of success using it?
I&
.icdm06long.pdf),
it's a simple greedy approach for selecting an ensemble from a library of
models of different parameters that maximize a given score function, I
would like to implement this as a part of the ensemble package of
scikit-learn?
I've already implemented an initial implementati
---
Get 100% visibility into Java/.NET code with AppDynamics Lite!
It's a free troubleshooting tool designed for production.
Get down to code-level detail for bottlenecks, with <2% overhead.
Download for free and get started troubleshooting in minutes.
http://pubads.g.doubleclic
> That's not even a very big matrix, it's less than 100MB. Does the
error occur even with n_jobs=2?
Yes.
--
Get 100% visibility into Java/.NET code with AppDynamics Lite!
It's a free troubleshoo
sed Sparse Row format>
--
Get 100% visibility into Java/.NET code with AppDynamics Lite!
It's a free troubleshooting tool designed for production.
Get down to code-level detail for bottlenecks, with <2% overhead.
Download for free an
least(n_jobs=2,3,4),
correct?
--
Get 100% visibility into Java/.NET code with AppDynamics Lite!
It's a free troubleshooting tool designed for production.
Get down to code-level detail for bottlenecks, with <2% overhead.
Download for free and get star
16 cores thought should use njobs=-1,
e.g. OnevsRestClassifier(SGDClassifier, njobs=-1) training completes in
about 20 min]
--
Get 100% visibility into Java/.NET code with AppDynamics Lite!
It's a free troubleshooting
> Use the predict_proba method, or decision_function, depending on the
> model (for SGD, decision_function always works). Btw., if you're not
> doing multilabel, then you don't need OneVsRestClassifier.
>
Thanks, will give it a shot.
On another note, n_jobs > 1 f
Hello,
For my ML problem I am facing a bit of dilemma wrt my solution
Problem: Predict a category using a text-classifier for large number of
categories. Depending on the category predicted we need some post
processing [e.g. get document with URL] and try to predict again
Hi, I'd like to improve ICA as discussed in #2113.
Also I'd like to inquire memory behavior of the decomposition classes to better
support their combined application on bog data sets with more than 100k samples.
Also I'd like to take a look at API inconsistencies between those cla
>
> I don't have the Bishop, and I must confess that I am still confused by
> the Wikipedia. That said, it doesn't really matter. As long as people
> feel confident that it is well defined and useful, it belongs to the
> scikit, and I am all for it :).
>
> Gael
>
>
>
Thank you all!
Let's hope it w
Hello All,
Sorry if it's stupid but it's not so obvious to me.
Is it possible to perform a factorial analysis with sklearn or do I have to
use other libraries?
Thanks and regards,
Joris
--
Keep Your Develo
22 matches
Mail list logo
