Virtual Labs

Random Forest is an example of which type of learning?

a: Unsupervised Explanation

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b: Reinforcement Explanation

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c: Supervised Explanation

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d: Semi-supervised Explanation

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What is the basic building block of a Random Forest?

a: Neural Network Explanation

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b: Support Vector Explanation

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c: Decision Tree Explanation

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d: Linear Model Explanation

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Which technique is used to create different trees in a Random Forest?

a: Gradient Descent Explanation

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b: Bagging Explanation

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c: Boosting Explanation

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d: Pruning Explanation

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What does the term 'Random' refer to in Random Forest?

a: Random class labels Explanation

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b: Random output prediction Explanation

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c: Random selection of data samples and features Explanation

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d: Random pruning of trees Explanation

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How does Random Forest reduce overfitting compared to a single Decision Tree?

a: By increasing tree depth Explanation

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b: By using only one feature Explanation

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c: By averaging predictions of multiple trees Explanation

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d: By removing training data Explanation

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Which parameter controls the number of trees in a Random Forest?

a: max_depth Explanation

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b: learning_rate Explanation

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c: n_estimators Explanation

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d: batch_size Explanation

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How are predictions combined in Random Forest classification?

a: Mean value Explanation

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b: Weighted sum Explanation

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c: Majority voting Explanation

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d: Gradient update Explanation

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Which type of problem can Random Forest solve?

a: Only classification Explanation

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b: Only regression Explanation

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c: Both classification and regression Explanation

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d: Only clustering Explanation

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Which feature of Random Forest helps reduce variance?

a: Feature scaling Explanation

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b: Data normalization Explanation

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c: Dimensionality reduction Explanation

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d: Ensemble learning Explanation

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What is the main purpose of using Out-of-Bag (OOB) samples in Random Forest?

a: To increase tree depth Explanation

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b: To estimate model performance without a separate validation set Explanation

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c: To normalize input features Explanation

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d: To remove noisy labels Explanation

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