ML Quiz 4

A regression model predicts _______ values

• discreate

• continuous

A classification model predicts ______ values.

• discrete

• continuous

A model defines the relationship _______

• among correlated features

• among features

• between features and label

• between rows and columns of the dataset

Inference means applying the trained model to unlabeled examples.

• True

• False

Suppose you want to develop a supervised machine learning model to predict whether a given email is "spam" or "not spam." Which of the following statements are true?

• We'll use unlabeled examples to train the model.

• The labels applied to some examples might be unreliable.

• Emails not marked as "spam" or "not spam" are unlabeled examples.

• Words in the subject header will make good labels.

Suppose an online shoe store wants to create a supervised ML model that will provide personalized shoe recommendations to users. That is, the model will recommend certain pairs of shoes to Marty and different pairs of shoes to Janet. The system will use past user behavior data to generate training data. Which of the following statements are true?

• "Shoes that a user adores" is a useful label.

• "The user clicked on the shoe's description" is a useful label.

• "Shoe size" is a useful feature.

• "Shoe beauty" is a useful feature.

In supervised learning, a machine learning algorithm builds a model by examining many examples and attempting to find a model that minimizes loss; this process is called ________

• activation function

• cost function

• empirical risk minimization.

• gradient descent

• lagloss function

If the model's prediction is perfect, the loss is greater; otherwise, the loss is zero.

• True

• False

The goal of training a model is to find a set of weights and biases that have low loss, on average, across all examples.

• True

• False

Which of the two data sets shown in the preceding plots has the lower Mean Squared Error (MSE)?

• The dataset on the left.

• The dataset on the right.