GATE DA Machine Learning PYQs & Answers

Questions 1–10 of 28. Imported answers require independent review unless marked reviewed.

For a classification problem, Principal Component Analysis (PCA) has been used to reduce the dimensionality of a feature space from 100 to 10.

Which of the following options is true about the angle

between the first and the tenth principal components?

Your answerChoose one option.

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Consider that you are training a classifier for a 10-class classification problem. Each input is represented as a 512-dimensional vector. There are 1000 samples, out of which first 100 will be used for testing. Let Leave-One-Out-Cross-Validation (LOOCV) be used for selection of the classifier model before testing.

Which of the following options is the correct number of validation splits that will be generated?

Your answerChoose one option.

512

900

1000

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In the following table, the Task column lists a few tasks related to machine learning. The Algorithm column lists a few algorithms.

Each entry “t” from the Task column is to be matched with an appropriate entry “a” from the Algorithm column such that the task “t” can be solved using the algorithm “a”. Denote such a match as t:a.

Task	Algorithm
T1 – Clustering	A1 – Markov Chain Monte Carlo
T2 – Classification	A2 – K-Medoid
T3 – Sampling	A3 – Linear Discriminant Analysis
T4 – Feature Extraction	A4 – Naive Bayes

Which of the following options is/are the correct matching(s)?

Your answerSelect all correct options. You can choose more than one.

T1:A4, T2:A3, T3:A1, T4:A2

T1:A2, T2:A4, T3:A1, T4:A3

T1:A3, T2:A4, T3:A1, T4:A2

T1:A4, T2:A2, T3:A1, T4:A3

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Consider that for a supervised learning task, the objective function being minimized is

, where

is the input and

is the parameter. Stochastic Gradient Descent with learning rate of 0.10 is used for parameter updates. Suppose that at the end of iteration

, the value of

becomes 10.00. Let

be the input for iteration

. The value of

at the end of iteration

is __________ . (Rounded off to two decimal places)

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Let four points in three-dimensional space be: P1: [2, 3, −1], P2: [3, 1, 1], P3: [5, −2, 3] and P4: [3, 3, 3]. Hierarchical Agglomerative Clustering is used to cluster the above points. If Manhattan Distance is used as the distance metric during clustering, which of the following options indicates the two points that will be merged first?

Your answerChoose one option.

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Which of the following statements is true for Ridge Regression?

Your answerChoose one option.

The regularizer in the objective function of Ridge Regression is used to guard against scenarios where the model works well for the test data, but poorly for the training data.

The regularizer of Ridge Regression uses

norm.

Ridge Regression aims to reduce the number of parameters that have negative values.

The regularizer of Ridge Regression may increase the bias of the model, but it helps in reducing the variance in predictions.

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Consider that 20 stories of Author X and 10 stories of Author Y were kept together without mentioning the names of the authors. A classifier was then asked to predict the author (X or Y) of each of these stories. Let, out of X’s stories, 6 were classified as that of Y. On the other hand, out of Y’s stories, 2 were classified as that of X.

Considering X and Y as two classes, which of the following statements is/are true?

Your answerSelect all correct options. You can choose more than one.

Accuracy of the classifier is 11/15.

Precision of Class X is higher than the Precision of Class Y.

Recall of Class X is higher than the Recall of Class Y.

Accuracy of the classifier is 14/15.

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Consider that Linear Ridge Regression is being used to learn a prediction function

, where

and Mean Absolute Error (MAE) is used to measure the prediction error. A weight of 0.20 is associated with the regularizer.

At an intermediate step of the training process, assume that the parameter

. In the next step, for the input

, the predicted value of

is noted. Let the relation between

and the true value of

The value of the overall regularized loss function for this instance is _____. (Rounded off to two decimal places)

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Consider a fully-connected feed-forward multi-layer perceptron. It has 30 neurons in the input layer, followed by two hidden layers and an output layer. The first hidden layer has 4 neurons and the second hidden layer has 3 neurons. The output layer has only one neuron. Assume that no bias parameters are used.

The number of learnable parameters in the multi-layer perceptron is __________ . (Answer in integer)

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Consider designing a linear classifier

on a dataset

. Recall that the sign function outputs +1 if the argument is positive, and −1 if the argument is non-positive. The parameters

and

are updated as per the following training algorithm:

whenever

. In other words, whenever the classifier wrongly predicts a sample

from the dataset,

gets updated to

, and likewise

gets updated to

. Consider the case

. Then

Your answerChoose one option.

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GATE DA Machine Learning PYQs

How to practice Machine Learning

Question 11

Question 12

Question 23

Question 29

Question 36

Question 37

Question 47

Question 55

Question 56

Question 22