Machine Learning Theories

What is the primary goal of supervised learning?

• Minimize errors in predictions

• Maximize computational efficiency

• Predict future events

• Learn from unlabeled data

What is cross-validation used for in machine learning?

• Cross-training different models

• Evaluating model performance on multiple datasets

• Selecting hyperparameters

• Testing a model's generalization ability

What's the difference between precision and recall, as matrices for model performance?

• Both measure the same thing

• Precision focuses on false positives, recall focuses on false negatives

• Precision focuses on false negatives, recall focuses on false postives

What's the primary purpose of a validation set in machine learning?

• To train the model

• To test the model

• To evaluate the model during training

• To compare multiple models

Which of the following is an example of a classification metric?

• Mean Absolute Error (MAE)

• Root Mean Squared Error (RMSE)

• Area Under the Receiver Operating Characteristic (ROC-AUC)

• R-squared (R2)

What is overfitting in the context of machine learning model?

• Fitting a model with insufficient data

• Fitting a model too closely to the training data

• Fitting a model with too few features

• Fitting a model to the validation set

What is the purpose of the K-nearest neighbors (KNN) algorithm?

• Clustering data into K groups

• Predicting a continuous output

• Classifying data based on its neighbors

• Reducing the dimensionality of features

Please name at least two machine learning models.