Confusion matrix

import matplotlib.pyplot as plt

import seaborn as sns

from sklearn import metrics

y_true = [0, 1, 2, 0, 1, 2, 0, 2, 2]

y_pred = [0, 2, 1, 0, 2, 1, 0, 0, 2]

cm = metrics.confusion_matrix(y_true, y_pred)

plt.figure(figsize=(10, 10))

cmap = sns.cubehelix_palette(50, hue=0.05, rot=0, light=0.9, dark=0,

as_cmap=True)

sns.set(font_scale=2.5)

sns.heatmap(cm, annot=True, cmap=cmap, cbar=False)

plt.ylabel('Actual Labels', fontsize=20)

plt.xlabel('Predicted Labels', fontsize=20)