• Supervised vs. Unsupervised Machine Learning:
• Supervised Learning: Models are trained on labeled datasets where inputs map to known target outputs:
• Support Vector Machine (SVM): Supervised classification/regression.
• Decision Tree: Supervised classification/regression.
• Linear Regression: Supervised continuous target regression.
• Unsupervised Learning: Models identify hidden patterns, clusters, or intrinsic groupings within unlabeled data without predefined ground truth.
• K-means clustering: Classic unsupervised partitioning algorithm that clusters data points into $K$ centroids based on distance metrics.
• Conclusion: K-means clustering is NOT a supervised learning method (Option 2).

Correct option: (2) K-means clustering

• Uncertainty in Artificial Intelligence Environments:
• According to Russell & Norvig's foundational AI framework, an agent faces an uncertain environment if the environment is:

• If the agent lacks complete state knowledge through its percepts, or if actions do not uniquely and deterministically determine the subsequent state, uncertainty inevitably arises.
• Conclusion: Not fully observable or not deterministic (Option 2).

Correct option: (2) Not fully observable or not deterministic

• Ensemble Modeling Techniques:
• Bagging (Bootstrap Aggregation): Trains multiple models independently on bootstrapped subsamples in parallel (e.g., Random Forest).
• Boosting: Trains models sequentially, where each successor model focuses on correcting residual errors of predecessor models (e.g., AdaBoost, XGBoost).
• Stacking (Stacked Generalization): Trains diverse base learners and uses a meta-model trained on cross-validated predictions to combine their outputs.
• Blending: A simplified heuristic variation of stacking that uses a single hold-out validation set rather than $k$-fold cross-validation. In standard academic machine learning curricula and competitive examinations, Blending is not classified as one of the fundamental theoretical ensemble architectures.
• Conclusion: Blending (Option 3).

Correct option: (3) Blending