# Importing libraries and modules import pandas as pd from utils import * from logistic_regression import LogisticRegressor # Reading data into variables. X = pd.read_csv("breast_data.csv", header=None).to_numpy() y = pd.read_csv("breast_truth.csv", header=None).to_numpy() # Splitting data into train/test sets X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2) # Creating model model = LogisticRegressor(learning_rate=0.0001, n_iterations=100) model.fit(X_train, y_train) # Predict test data for evaluate model predict_test = model.predict(X_test) print("Accuracy of model on test data: %2.2f" % accuracy(y_test, predict_test))