from sklearn.cross_validation import StratifiedKFold def load_data(): # load your data using this function def create model(): # create your model using this function def train_and_evaluate__model(model, data[train], labels[train], data[test], labels[test)): model.fit... # fit and evaluate here. if __name__ == "__main__": n_folds = 10 data, labels, header_info = load_data() skf = StratifiedKFold(labels, n_folds=n_folds, shuffle=True) for i, (train, test) in enumerate(skf): print "Running Fold", i+1, "/", n_folds model = None # Clearing the NN. model = create_model() train_and_evaluate_model(model, data[train], labels[train], data[test], labels[test))
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