ml-finance-python

python scripts for finance machine learning

git clone https://9o.is/git/ml-finance-python.git

decision_tree_regressor.py

(1599B)

      1 from __future__ import division, print_function
      2 import numpy as np
      3 import matplotlib.pyplot as plt
      4 import pandas as pd
      5 
      6 from mlfromscratch.utils import train_test_split, standardize, accuracy_score
      7 from mlfromscratch.utils import mean_squared_error, calculate_variance, Plot
      8 from mlfromscratch.supervised_learning import RegressionTree
      9 
     10 def main():
     11 
     12     print ("-- Regression Tree --")
     13 
     14     # Load temperature data
     15     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
     16 
     17     time = np.atleast_2d(data["time"].values).T
     18     temp = np.atleast_2d(data["temp"].values).T
     19 
     20     X = standardize(time)        # Time. Fraction of the year [0, 1]
     21     y = temp[:, 0]  # Temperature. Reduce to one-dim
     22 
     23     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
     24 
     25     model = RegressionTree()
     26     model.fit(X_train, y_train)
     27     y_pred = model.predict(X_test)
     28 
     29     y_pred_line = model.predict(X)
     30 
     31     # Color map
     32     cmap = plt.get_cmap('viridis')
     33 
     34     mse = mean_squared_error(y_test, y_pred)
     35 
     36     print ("Mean Squared Error:", mse)
     37 
     38     # Plot the results
     39     # Plot the results
     40     m1 = plt.scatter(366 * X_train, y_train, color=cmap(0.9), s=10)
     41     m2 = plt.scatter(366 * X_test, y_test, color=cmap(0.5), s=10)
     42     m3 = plt.scatter(366 * X_test, y_pred, color='black', s=10)
     43     plt.suptitle("Regression Tree")
     44     plt.title("MSE: %.2f" % mse, fontsize=10)
     45     plt.xlabel('Day')
     46     plt.ylabel('Temperature in Celcius')
     47     plt.legend((m1, m2, m3), ("Training data", "Test data", "Prediction"), loc='lower right')
     48     plt.show()
     49 
     50 
     51 if __name__ == "__main__":
     52     main()