Re: [Scikit-learn-general] RandomizedSearchCV error

It's a problem of excessive memory consumption due to a O(# possible parameter settings) approach to sampling from discrete parameter grids without replacement. The fix was merged into master only hours ago. Please feel free to work with master, or to cherry-pick febefb0 On 25 June 2015 at 16:22,

[Scikit-learn-general] RandomizedSearchCV error

This code that uses RandomizedSearchCV works fine in 0.15.2: import pandas as pd from sklearn.pipeline import Pipeline from sklearn.datasets import load_iris from sklearn.ensemble import RandomForestClassifier from sklearn.grid_search import RandomizedSearchCV iris = load_iris() X = iris.data y =

Re: [Scikit-learn-general] Passing kwargs to pipeline predict

What estimators have predict with multiple args? Without support for same in cross validation routines and scorers, isn't t easier to write this functionality in custom code as you need it, leaving the predictor off the Pipeline? On 25 June 2015 at 06:06, Michael Kneier wrote: > Hi all, > > It d

[Scikit-learn-general] Passing kwargs to pipeline predict

Hi all, It doesn't look like pipelines currently support passing kwargs to their estimators' predict method. I think it would be great to add this functionality, but I want to get your thoughts before I open a PR. Thanks, Mike --

Re: [Scikit-learn-general] RandomForestClassifier with warm_start and n_jobs

Hi Dale Thanks for the code sample! Indeed, warm_start does not disable parallelization, I can confirm by both running your code and checking the source. Moreover, that example you mentioned was added on May, 2nd, and it doesn't look

[Scikit-learn-general] ANN: Last Call for SciPy 2015 Registration (Scientific Python Conference - July 8-10)

Last Call to Register for SciPy 2015 (Scientific & Analytic Python Conference) Main conference July 8-10, tutorials July 6-7 & coding sprints July 11-12!Here are just a few reasons you don't want to miss this year's SciPy Conference (Online regis

[Scikit-learn-general] RandomForestClassifier with warm_start and n_jobs

Hello, Version 0.16.1 adds warm_start to RandomForestClassifier, but the documentation doesn't include a note that warm_start disables parallelization. I found a reference to this in a comment in the "OOB Errors for Random Forests" example in the development documentation. http://scikit-learn.