Virtual Labs

Which kernel is best suited for the two-moons dataset?

a: Linear Explanation

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b: Polynomial Explanation

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c: RBF Explanation

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d: Sigmoid Explanation

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What does parameter C control in SVM?

a: Kernel type Explanation

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b: Regularization strength Explanation

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c: Learning rate Explanation

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d: Feature scaling Explanation

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What does the diagonal of a confusion matrix represent?

a: Errors Explanation

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b: Correct classifications Explanation

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c: Precision Explanation

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d: Recall Explanation

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What does StandardScaler() do?

a: Normalizes to [0,1] Explanation

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b: Removes outliers Explanation

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c: Standardizes to zero mean and unit variance Explanation

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d: Converts categorical data Explanation

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Which parameter controls margin softness?

a: Gamma Explanation

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b: Degree Explanation

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c: C Explanation

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d: Kernel Explanation

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High gamma in RBF results in:

a: Underfitting Explanation

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b: Overfitting Explanation

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c: Linear separation Explanation

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d: Increased margin width Explanation

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SVM guarantees:

a: Local optimum Explanation

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b: Global optimum Explanation

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c: Random solution Explanation

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d: Heuristic result Explanation

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The RBF kernel maps data into:

a: Lower dimension Explanation

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b: Same dimension Explanation

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c: Higher-dimensional feature space Explanation

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d: Binary space Explanation

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SVM performs best when:

a: Data is noisy Explanation

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b: Classes are overlapping Explanation

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c: Margin is maximized Explanation

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d: Features are unscaled Explanation

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Generalization refers to:

a: Optimal performance on training data Explanation

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b: Optimal performance on unseen data Explanation

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c: Fast training speed Explanation

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d: Less model size Explanation

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Support Vector Machine (SVM)