ml-finance-python

k_nearest_neighbors.py

(851B)

 from __future__ import print_function
 import numpy as np
 import matplotlib.pyplot as plt
 from sklearn import datasets
 
 from mlfromscratch.utils import train_test_split, normalize, accuracy_score
 from mlfromscratch.utils import euclidean_distance, Plot
 from mlfromscratch.supervised_learning import KNN
 
 def main():
     data = datasets.load_iris()
     X = normalize(data.data)
     y = data.target
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33)
 
     clf = KNN(k=5)
     y_pred = clf.predict(X_test, X_train, y_train)
     
     accuracy = accuracy_score(y_test, y_pred)
 
     print ("Accuracy:", accuracy)
 
     # Reduce dimensions to 2d using pca and plot the results
     Plot().plot_in_2d(X_test, y_pred, title="K Nearest Neighbors", accuracy=accuracy, legend_labels=data.target_names)
 
 
 if __name__ == "__main__":
     main()