%load_ext autoreload
%autoreload 2
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
The autoreload extension is already loaded. To reload it, use: %reload_ext autoreload
plt.rcParams['figure.figsize'] = [14, 9]
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)
LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True, intercept_scaling=1, l1_ratio=None, max_iter=1000, multi_class='multinomial', n_jobs=None, penalty='l2', random_state=None, solver='lbfgs', tol=0.0001, verbose=0, warm_start=False)
from sklearn_plot_api import plot_confusion_matrix
viz = plot_confusion_matrix(clf, X, y)
viz.im_.set_cmap('plasma')
viz.figure_
viz.plot(cmap='plasma')
<sklearn_plot_api.confusion_matrix.ConfusionMatrixViz at 0x1a1db1b358>
viz.plot(include_values=True)
<sklearn_plot_api.confusion_matrix.ConfusionMatrixViz at 0x1a1db1b358>