What is the fundamental difference between classification algorithms and clustering?

The key difference between classification and clustering is that classification is a supervised task, where we have labeled data (class labels), and the model learns to predict these labels for new objects. Clustering is an unsupervised task, where we try to find natural groups (clusters) in the data without pre-existing labels.

Example:

• Classification: determining which type of flower a sample belongs to, given a training set with labels.
• Clustering: dividing customers into groups based on similar behavior without pre-known categories.

In Python, classification often uses libraries like sklearn with algorithms such as LogisticRegression, RandomForest, while clustering uses KMeans, DBSCAN.