In [1]:

    

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

data = [(0.01, 3, 2.786318e-01), #learning rate, depth, R^2
       (0.01, 5, 3.309793e-01),
       (0.01, 7,3.545946e-01),
       (0.1, 3, 4.494290e-01),
       (0.1, 5, 4.848307e-01),
       (0.1, 7, 0.500908),
        (0.05, 10, 0.508588),
        (0.08, 10, 0.505968),
        (0.3, 7, 0.450216),
       (1, 3, 1.792066e-02),
        (1,5, 1.198566e-01),
       (1,7, -1.649937e-01),
       (10, 3, -1.796564e+190),
       (10, 5, -2.579831e+190),
       (10, 7, -4.126538e+190)]


    

In [3]:

    

temp = pd.DataFrame(data)
temp[2] = temp[2].apply(lambda x: 0 if x<0 else x)
temp = temp.pivot(index=0, columns=1, values=2)


    

In [4]:

    

plt.figure()
ax = sns.heatmap(temp)
plt.xlabel('Max Depth')
plt.ylabel('Learning Rate')
plt.show()


    

    






<matplotlib.figure.Figure at 0x2ba3add8240>






    

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