ml-finance-python

linear_discriminant_analysis.py

(929B)

 from __future__ import print_function
 from sklearn import datasets
 import matplotlib.pyplot as plt
 import numpy as np
 
 from mlfromscratch.supervised_learning import LDA
 from mlfromscratch.utils import calculate_covariance_matrix, accuracy_score
 from mlfromscratch.utils import normalize, standardize, train_test_split, Plot
 from mlfromscratch.unsupervised_learning import PCA
 
 def main():
     # Load the dataset
     data = datasets.load_iris()
     X = data.data
     y = data.target
 
     # Three -> two classes
     X = X[y != 2]
     y = y[y != 2]
 
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33)
 
     # Fit and predict using LDA
     lda = LDA()
     lda.fit(X_train, y_train)
     y_pred = lda.predict(X_test)
 
     accuracy = accuracy_score(y_test, y_pred)
 
     print ("Accuracy:", accuracy)
 
     Plot().plot_in_2d(X_test, y_pred, title="LDA", accuracy=accuracy)
 
 if __name__ == "__main__":
     main()