def run_iris(): # Load iris data set iris = datasets.load_iris() n_inputs = len(iris.data[0]) n_outputs = len(iris.target_names) network = NeuralNetwork() network.create_network(n_inputs, n_outputs, (3, 4)) data_scaled = preprocessing.scale(iris.data) print("Their neural network results: {}".format(cross_val_score(nn, data_scaled, iris.target, 3))) print("My neural network results: {}".format(cross_val_score(network, data_scaled, iris.target, 3)))
def run_diabetes(): data = [] target = [] # Read data with open('pima-indians-diabetes.data') as diabetes_file: diabetes_reader = csv.reader(diabetes_file, quoting=csv.QUOTE_NONNUMERIC) for row in diabetes_reader: data.append(row[:8]) target.append(int(row[8])) n_inputs = len(data[0]) n_outputs = len(set(target)) network = NeuralNetwork() network.create_network(n_inputs, n_outputs, (3, 4)) data_scaled = preprocessing.scale(np.array(data)) print("Neural network results accuracy: {}".format(cross_val_score(network, data_scaled, np.array(target), 3)))