Machine Learning Quiz

In gradient descent, The gradient is actually a scalar times the coordinates of the point!

What does

the Scalar signify? (Select all that apply)

• Closer the label to the prediction, the larger the gradient

• Closer the label to the prediction, the Smaller the gradient

• Farther the label from the prediction, the Larger the gradient

• Farther the label to the prediction, the Smaller the gradient

What do I need to add to get my SVM classifier below running?

• Nothing more is needed

• Normalizing and splitting the datasets

• Fitting the classifier and making a list of predictors

images for cat recognition is an example of "structured" data because it is represented as a structured array in the computer. True/False?

• True

• False

This picture is a result of ?

• Supervised Learning; Classification

• Unsupervised Learning; Regression

• Unsupervised Learning; Prediction

• Supervised Learning; Regression

Suppose we have a dataset that can be trained with 100% accuracy with the help of a decision tree of depth 6.

Now consider the points below and choose your option based on these points:

1. Depth 4 will have high bias and low variance

2. Depth 4 will have low bias and low variance

• only 1

• only 2

• Both 1 and 2

• None of the above

So we were plotting the visualization for different values of C (Penalty Parameter) in the SVM algorithm. Due to some reason, we forgot to tag the C values with visualizations. In that case which of the following options best explains the C values for the images below (1,2,3 left to right, so C values are C1 for image 1, C2 for image 2, and C3 for image 3) in case of rbf kernel.

• C1 = C2 = C3

• C1 > C2 > C3

• C1 < C2 < C3

• None of these