from sklearn.neural_network import MLPClassifier import os from models.model import Model from models.test import Test from sklearn.feature_selection import chi2, f_classif pd.set_option('display.max_columns', 500) to_drop = ["ht", "at", "Unnamed: 0"] results = "home_team_won" clf = MLPClassifier(hidden_layer_sizes=(10, 10, 10), max_iter=1000) data = os.path.abspath("../data/big_data.csv") print(data) clf = Model(clf, data) clf.drop_columns(to_drop) clf.get_X_y(results) clf.to_numerical() #tester = Test(clf) #tester.test_k_best() #clf.feature_corr() clf.k_best(f_classif, 8) clf.split_data(0.2) clf.standard_scale() clf.lda(1) clf.fit_clf() clf.pred_clf() ac, cm, cr = clf.eval_clf()