Kmeans clustering
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
import pandas as pd
data = pd.read_csv("data.csv") # Load dataset (ensure data.csv is available)
X = data.iloc[:, :].values # Use all columns as features
kmeans = KMeans(n_clusters=3, random_state=42).fit(X) # Apply K-Means with 3 clusters
labels = kmeans.labels_ # Cluster labels for each data point
plt.scatter(X[:, 0], X[:, 1], c=labels, cmap='viridis') # Visualize clusters
plt.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:, 1], color='red', marker='x') # Centers
plt.title("K-Means Clustering")
plt.show()
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