yb_subplots.py

import matplotlib.pyplot as plt

from yellowbrick.datasets import load_occupancy
from yellowbrick.model_selection import CVScores
from yellowbrick.classifier import ConfusionMatrix

from sklearn.svm import SVC
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import train_test_split as tts

# Load a sample dataset and make train and test splits
X, y = load_occupancy()
X_train, X_test, y_train, y_test = tts(X, y, test_size=0.2, shuffle=True)

# Create 2 side-by-side subplots
fig, axes = plt.subplots(ncols=2, figsize=(8, 4))

# Instantiate the ConfusionMatrix visualizer for an SVM model
svm_confusion_matrix = ConfusionMatrix(
    SVC(),
    classes=["Occupied", "Vacant"],
    cmap="GnBu",
    ax=axes[0]
)
svm_confusion_matrix.fit(X_train, y_train)
svm_confusion_matrix.score(X_test, y_test)

# Create a cross-validation strategy
strategy = StratifiedKFold(n_splits=12, shuffle=True)

# Instantiate the CVScores visualizer for an SVM model
svm_cv_scores = CVScores(
    SVC(),
    scoring="f1_weighted",
    cv=strategy,
    ax=axes[1]
)
svm_cv_scores.fit(X, y)

fig.suptitle("Performance of an SVM model on the occupancy dataset")
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
plt.show()