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()
