Regression Training Quiz

What is the process for training a regression model?

• Split the training data, use an algorithm to fit the training data to a model, use the validation data to test the model, compare the known actual labels to the predicted labels

• Use an algorithm to fit the training data to a model, compare the known actual labels to the predicted labels, repeat the process with different algorithms and parameters

• Use the validation data to test the model, compare the known actual labels to the predicted labels, use an algorithm to fit the training data to a model

• Split the training data, use an algorithm to fit the training data to a model, repeat the process with different algorithms and parameters

What is the algorithm used to fit the training data to a regression model?

• Logistic Regression

• Linear Regression

• Decision Tree

• K-Nearest Neighbors

What is the function derived by the linear regression algorithm in the ice cream sales example?

• f(x) = x/50

• f(x) = x*50

• f(x) = x-50

• f(x) = x+50

What is the metric that measures the proportion of variance in the validation results that can be explained by the model?

• Coefficient of determination (R2)

• Root Mean Squared Error (RMSE)

• Mean Squared Error (MSE)

• Mean Absolute Error (MAE)

What does the Root Mean Squared Error (RMSE) measure?

• The mean of the squared absolute values

• The average of the absolute errors

• The square root of the MSE

• The proportion of variance explained by the model

What is varied in the iterative training process of a regression model?

• Feature selection and preparation, Algorithm selection, Algorithm parameters

• Feature selection and preparation, Data cleaning, Model deployment

• Algorithm selection, Model evaluation, Data visualization

• Algorithm parameters, Data preprocessing, Model training

What is the purpose of holding back a subset of the data for validation in the training process?

• To increase the training data size

• To test the model by predicting labels for the features

• To compare the known actual labels to the predicted labels

• To refine the model by repeating the training process

What is the mean absolute error (MAE) for the ice cream sales example?

• 2.45

• 6

• 0.95

• 2.33

What is the mean squared error (MSE) for the ice cream sales example?

• 2.45

• 6

• 2.33

• 0.95

What is the coefficient of determination (R2) for the ice cream sales example?

• 2.45

• 6

• 2.33

• 0.95