Created
April 28, 2014 06:22
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A python script that causes deadlocks in ipython
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import sklearn as sk | |
import numpy as np | |
import pandas as pd | |
import scipy as scipy | |
import cPickle as pickle | |
import math | |
from collections import Counter | |
from sklearn.cross_validation import train_test_split | |
from sklearn.cross_validation import cross_val_score | |
from sklearn.cross_validation import ShuffleSplit | |
from scipy.stats import sem | |
from scipy.stats.mstats import mode | |
from sklearn.grid_search import GridSearchCV | |
from sklearn.ensemble import RandomForestClassifier | |
def do_gs(model, params, n_samples=1000, cv=3, n_jobs=-1): | |
gs = GridSearchCV(model, params, cv=cv, n_jobs=n_jobs, verbose=2) | |
gs.fit(X_train[:n_samples], y_train[:n_samples]) | |
print(gs.best_params_, gs.best_score_) | |
return gs | |
f = open( "../data/all_data.p", "rb" ) | |
data = pickle.load(f) | |
f.close() | |
seed = 0 | |
X_train = data['train_munged']; | |
y_train = data['y']; | |
%del data | |
print "Loaded train[" + `len(X_train)` + "]" | |
data = { 'min_samples_leaf': [1, 2, 3, 4, 5], 'min_samples_split': [4, 5, 6], | |
'max_depth': [21, 22, 23, 24], 'max_features': [36, 37, 38, 39, 40], | |
'n_estimators': [470, 475, 480] } | |
gs = do_gs(RandomForestClassifier(random_state=seed, n_jobs=1), | |
data, cv=3, n_samples=2500, n_jobs=30) |
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