Supervised Learning Models

Test your knowledge of regression and classification algorithms in scikit-learn.

1. Which supervised learning task involves predicting continuous output values?

Classification Regression Clustering Dimensionality Reduction

2. Which of the following are classification algorithms?

Support Vector Machines (SVM) Linear Regression Random Forest K-Nearest Neighbors (K-NN)

3. Logistic Regression is used for regression tasks.

True False

4. What does the acronym 'K-NN' stand for in supervised learning?

5. Which model uses a tree-like structure with decision nodes to make predictions?

Naive Bayes Decision Tree Linear Regression PCA

6. Which of the following are regularization techniques used in regression to prevent overfitting?

L1 Regularization (Lasso) L2 Regularization (Ridge) Dropout Early Stopping

7. Random Forest is an ensemble method that combines multiple decision trees.

True False

8. Name the algorithm that models the probability of a target variable given input features using Bayes' theorem.

9. Which supervised learning task assigns input data to predefined categories?

Regression Clustering Classification Dimensionality Reduction

10. What is the term for the input variables used to predict the target in supervised learning?

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