Machine Learning, Data Science, Artificial Intelligence, Programming, Technology.
""" This method performs the sigmoid function on param X and Returns the outcome as a varible called y""" y = 1 / (1 + np.exp(-Beta_1*(X-Beta_2))) return y Let’s now test our sigmoid function with some sample values beta_1 = 0.10 beta_2 = 1990.0 # logistic_function y_pred = sigmoid(X_data, beta_1,