Virtual Labs

In this experiment, the KNN classifier was trained using which dataset?

a: Wine dataset Explanation

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b: Iris dataset Explanation

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c: MNIST dataset Explanation

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d: CIFAR-10 dataset Explanation

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How many features were used as input variables in the KNN model for this experiment?

a: 2 Explanation

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b: 3 Explanation

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c: 4 Explanation

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d: 5 Explanation

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In the experiment, the dataset was divided into training and testing sets using which ratio?

a: 50:50 Explanation

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b: 70:30 Explanation

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c: 80:20 Explanation

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d: 90:10 Explanation

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Why was StandardScaler used before training the KNN model?

a: To increase the number of samples Explanation

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b: To normalize feature ranges for fair distance calculation Explanation

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c: To remove missing values Explanation

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d: To change class labels Explanation

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What does the parameter k represent in the KNN classifier used in this experiment?

a: The number of clusters in the dataset Explanation

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b: The number of nearest neighbours considered for prediction Explanation

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c: The number of features used in the dataset Explanation

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d: The number of training samples in the dataset Explanation

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In this experiment, the confusion matrix was used to:

a: Increase model accuracy Explanation

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b: Visualize correct and incorrect predictions for each class Explanation

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c: Scale feature values Explanation

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d: Split the dataset into training and testing sets Explanation

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Which evaluation metric indicates the overall proportion of correctly classified samples?

a: Precision Explanation

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b: Recall Explanation

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c: Accuracy Explanation

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d: F1-Score Explanation

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ROC-AUC in this experiment was computed using which strategy?

a: One-vs-Rest (OvR) Explanation

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b: Linear regression Explanation

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c: Clustering method Explanation

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d: Gradient descent optimization Explanation

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Based on the experiment results, high accuracy indicates that:

a: The classifier correctly predicts most samples in the dataset Explanation

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b: The dataset size increases Explanation

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c: The number of features changes Explanation

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d: The model becomes unsupervised Explanation

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Why is stratified sampling used while splitting the dataset in this experiment?

a: To increase the number of samples in the dataset Explanation

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b: To ensure each class is proportionally represented in training and testing sets Explanation

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c: To reduce the number of features in the dataset Explanation

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d: To normalize the feature values Explanation

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k-Nearest Neighbors (KNN)