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from sklearn.datasets import load_breast_cancer

from sklearn.cluster import KMeans

from sklearn.preprocessing import StandardScaler

from sklearn.decomposition import PCA

from sklearn.metrics import confusion_matrix, classification_report

import matplotlib.pyplot as plt

X, y = load_breast_cancer(return_X_y=True)

X = StandardScaler().fit_transform(X)

y_pred = KMeans(n_clusters=2, random_state=42, n_init=10).fit_predict(X)

print(confusion_matrix(y, y_pred))

print(classification_report(y, y_pred))

X_pca = PCA(2).fit_transform(X)

plt.scatter(*X_pca.T, c=y_pred, cmap='coolwarm', alpha=0.7)

plt.title("K-Means Clustering (PCA)")

plt.show()




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