Hi, Howard,
I have no experience with Windows in particular, but installing libraries from
the Sci-stack (SciPy, NumPy) is usually a little bit of a hassle on every
platform. I can only highly recommend you looking at Anaconda, a Python
distribution for scientific computing — it’s free. 99% of t
I suspect supporting PMML import is a separate and low-priority project.
Higher priority is support for transformers (in pipelines / feature
unions), other predictors, and tests that verify the model against an
existing PMML predictor.
On 21 August 2015 at 01:37, Dale Smith wrote:
> Package skle
Hi. I am attempting to install scikit-learn on my Windows 7 laptop on
which I'm running Cygwin. I want to be able to
use scikit-learn from within a Cygwin window. I have Python 3.4 and
numpy installed. However, I am having trouble installing scipy and
this obviously may be related.
>pip instal
Package sklearn_pmml appeared on github:
https://github.com/alex-pirozhenko/sklearn-pmml
It's still in the early stages. I have yet to experiment with it, and I don't
think it supports pmml import.
Dale Smith, Ph.D.
Data Scientist
d. 404.495.7220 x 4008 f. 404.795.7221
Nexidia Corporate |
It sounds like you prefer false negatives over false positives (not
catching bad activity, but rarely misclassifying good activity as bad
activity). You can weight the different classes currently by setting the
sample weight on good activity points to be higher than those of bad
activity points. Th
Very nice! Thanks to both of you, Jacob and Andreas!
Andreas, yes, I'm interested in all leafs. The additional Pandas query done
on each leaf node is a further check to inspect whether this leaf node can
be of interest or not.
Binary classification for example, fraud detection to be more specific
Hi fellows,
I found some numbers generated are not right, and it took me half a day of
debugging. Finally, I found it was due to the loaded CSV file contains
special characters for a few categorical features. These categorical values
are all in UNICODE in different languages, Hindi, Chinese, Engli
hi,
> Agreed—this is exactly the type of use case I want to support.
> Pickling won't work here, but using HDF5 like MNE does would
> probably be close to ideal (thanks to Chris Holdgraf for the
> heads-up):
>
> https://github.com/mne-tools/mne-python/blob/master/mne/_hdf5.py
For your info Eric L
