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Tools of sklearn. Grid Search with multiprocess

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Usage Sample ''''''''''''

.. code:: python

import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearntools import train_evaluate, search_model_params

if __name__ == '__main__':
     X, y = np.arange(20).reshape((10, 2)), range(10)
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)

     model = RandomForestClassifier(n_estimators=837, bootstrap=False)
     train_evaluate(model, X_train, X_test, y_train, y_test)

     param_grid = {'n_estimators': np.arange(800, 820, 1), 'bootstrap': [False, True]}
     search_model_params(RandomForestClassifier, X_train, X_test, y_train, y_test, param_grid, result_num=3)

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