Machine Learning Supervised Learning 5

Question 1

What is 'data leakage' in a supervised learning pipeline?

Accepted Answer

Information from the test set inadvertently influencing model training

Answer

Data leakage occurs when information outside the training set (e.g., from the test set) is used during training, causing artificially inflated performance metrics.

Question 2

Which of the following is NOT a hyperparameter of a Random Forest model?

Accepted Answer

Learned feature weights of the trees

Answer

Learned feature weights are parameters determined by the training process, not hyperparameters set before training.

Question 3

When using one-hot encoding for categorical features, what problem can arise with high-cardinality variables?

Accepted Answer

Dimensionality explosion with many sparse binary columns

Answer

High-cardinality categorical variables create an extremely large and sparse feature matrix when one-hot encoded, increasing memory and computation costs.

Question 4

In multi-class classification with a neural network, which output activation function is most commonly used?

Accepted Answer

Softmax

Answer

Softmax outputs a probability distribution over all classes (summing to 1), making it suitable for multi-class classification output layers.

Question 5

What is the 'elbow method' used for in supervised learning?

Accepted Answer

Selecting the best k value for k-NN by plotting error vs. k

Answer

The elbow method plots validation error against different k values in k-NN; the optimal k is at the 'elbow' where error stops decreasing significantly.

Machine Learning Practice Test

Machine Learning Practice Test

Machine Learning Supervised Learning 5