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from sklearn.datasets import make_classification | |
from sklearn.linear_model import RandomizedLogisticRegression | |
import pandas as pd | |
clf = RandomizedLogisticRegression(sample_fraction = .75, n_resampling = 3, normalize = False) | |
X, y = make_classification(n_samples=10, | |
n_features=3, | |
n_informative=2, | |
n_redundant=0, | |
n_repeated=0, | |
n_classes=2, | |
random_state=123, | |
shuffle=False) | |
clf.fit(X,y) | |
data = pd.read_csv("~/dev/tmp/demo_model_data.csv") | |
y = data['dep_var'] | |
X = data.ix[:, 2:] | |
clf.fit(X,y) | |
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