#!/usr/bin/env python
# coding: utf-8

# In[4]:


get_ipython().run_line_magic('load_ext', 'autoreload')
get_ipython().run_line_magic('autoreload', '2')

get_ipython().run_line_magic('matplotlib', 'inline')

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


# In[5]:


plt.rcParams['figure.figsize'] = [14, 9]


# In[6]:


from sklearn.datasets import make_classification
from sklearn.linear_model import LogisticRegression

X, y = make_classification(n_samples=1000, n_informative=5, n_classes=10, random_state=0)
clf = LogisticRegression(solver='lbfgs', max_iter=1000, multi_class='multinomial')
clf.fit(X, y)


# In[8]:


from sklearn_plot_api import plot_confusion_matrix


# ## First plot

# In[9]:


viz = plot_confusion_matrix(clf, X, y)


# ## Change cmap

# In[10]:


viz.im_.set_cmap('plasma')
viz.figure_


# In[11]:


viz.plot(cmap='plasma')


# ## Include values

# In[12]:


viz.plot(include_values=True)