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Machine Learning Quiz

Total questions: 6

Worksheet time: 12mins

Name
Class
Date
1.

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

What does

the Scalar signify? (Select all that apply)

a)

Closer the label to the prediction, the larger the gradient

b)

Closer the label to the prediction, the Smaller the gradient

c)

Farther the label from the prediction, the Larger the gradient

d)

Farther the label to the prediction, the Smaller the gradient

2.

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

a)

Nothing more is needed

b)

Normalizing and splitting the datasets

c)

Fitting the classifier and making a list of predictors

3.

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

a)

True

b)

False

4.

This picture is a result of ?

a)

Supervised Learning; Classification

b)

Unsupervised Learning; Regression

c)

Unsupervised Learning; Prediction

d)

Supervised Learning; Regression

5.

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

a)

only 1

b)

only 2

c)

Both 1 and 2

d)

None of the above

6.

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.

a)

C1 = C2 = C3

b)

C1 > C2 > C3

c)

C1 < C2 < C3

d)

None of these