This is the main of the AdaBoost algorithm. It contains a raw data of 10 point from 2 class. """ from adaboost import AdaBoost import pandas as pd import numpy as np from matplotlib import pyplot as plt data = pd.DataFrame(np.array([[88, 144, 1], [93, 232, 1], [136, 275, -1], [147, 131, -1], [159, 69, 1], [214, 31, 1], [214, 152, -1], [257, 83, 1], [307, 62, -1], [307, 231, -1]]), columns=["x", "y", "label"]) def display(): f1 = plt.figure(1) positive = data[data["label"] == 1] negative = data[data["label"] == -1] plt.scatter(positive.iloc[:, 0], positive.iloc[:, 1], c="red", marker="+") plt.scatter(negative.iloc[:, 0], negative.iloc[:, 1], c="green") plt.show() if __name__ == '__main__': m_ada = AdaBoost(data, 5) display() m_ada.train() m_ada.display()