Python sklearn.grid_search() Examples

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Example #1
Source File: classify_shark.py    From ibeis with Apache License 2.0 6 votes vote down vote up 
def fit_new_classifier(problem, train_idx):
        """
        References:
            http://leon.bottou.org/research/stochastic
            http://blog.explainmydata.com/2012/06/ntrain-24853-ntest-25147-ncorrupt.html
            http://scikit-learn.org/stable/modules/svm.html#svm-classification
            http://scikit-learn.org/stable/modules/grid_search.html
        """
        print('[problem] train classifier on %d data points' % (len(train_idx)))
        data = problem.ds.data
        target = problem.ds.target
        x_train = data.take(train_idx, axis=0)
        y_train = target.take(train_idx, axis=0)
        clf = sklearn.svm.SVC(kernel=str('linear'), C=.17, class_weight='balanced',
                              decision_function_shape='ovr')

        # C, penalty, loss
        #param_grid = {'C': [1e3, 5e3, 1e4, 5e4, 1e5],
        #              'gamma': [0.0001, 0.0005, 0.001, 0.005, 0.01, 0.1], }
        #param_grid = {'C': [1e3, 5e3, 1e4, 5e4, 1e5],
        #              'gamma': [0.0001, 0.0005, 0.001, 0.005, 0.01, 0.1], }
        #clf = GridSearchCV(SVC(kernel='rbf', class_weight='balanced'), param_grid)
        #clf = clf.fit(X_train_pca, y_train)
        clf.fit(x_train, y_train)
        return clf