What will be the output of the following code? import pandas as pd from sklearn.preprocessing import StandardScaler data = pd.DataFrame({ 'col1': [1, 2, 3, 4, 5], 'col2': [10, 20, 30, 40, 50] }) ss = StandardScaler() scaled_data = ss.fit_transform(data) print(ss.var_)

(A) Option figure from the original question paper

(B) Option figure from the original question paper

(C) Option figure from the original question paper

(D) Option figure from the original question paper

MLP End Term: 13 April 2025, Set QDD1 (January 2025 term)

Question 1

+1 markOne correct option

Given the following code snippet that preprocesses a dataset with both continuous and categorical features using sklearn.preprocessing tools, what will be the first row of the X_transformed array after preprocessing?

python

1import numpy as np
2from sklearn.preprocessing import MinMaxScaler, OneHotEncoder
3from sklearn.compose import ColumnTransformer
4
5
6X = np.array([[2.0, 'apple'],
7              [5.0, 'banana'],
8              [1.0, 'apple'],
9              [4.0, 'cherry']])
10
11preprocessor = ColumnTransformer(
12                transformers=[('num', MinMaxScaler(), [0]),
13                              ('cat', OneHotEncoder(), [1])])
14
15X_transformed = preprocessor.fit_transform(X)
16print(X_transformed[0])

Question 2

+1 markOne correct option

What will be the output of the following code?

python

1import pandas as pd
2from sklearn.preprocessing import StandardScaler
3
4data = pd.DataFrame({
5    'col1': [1, 2, 3, 4, 5],
6    'col2': [10, 20, 30, 40, 50]
7})
8
9ss = StandardScaler()
10
11scaled_data = ss.fit_transform(data)
12print(ss.var_)

Question 3

+1 markOne correct option

Imagine you are using a Dummy Regressor with strategy=median. Given the following dataset:

S.No	$X_1$	$X_2$	$X_3$	$Y$
1	2.3	4.5	3.2	10.5
2	1.8	3.2	4.1	12.3
3	2.5	4.1	2.9	11.1
4	2.0	3.8	3.5	9.8
5	1.9	3.6	3.0	10.9
6	2.4	4.2	3.3	11.5

What will be the predicted output for an input X = [2.1,3.9,3.2] ?

A
10.5
B
11.0
C
11.5
D
12.3

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More on the MLP End Term 13 Apr 2025 Set QDD1 paper

The IIT Madras BS Machine Learning Practice (MLP) End Term paper sat on 13 Apr 2025, in the January 2025 term, set QDD1: 30 questions for 50 marks in 180 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.

Feature	MLP End Term 13 Apr 2025 Set QDD1 at a glance
Term	January 2025 term
Subject	Machine Learning Practice
Course code	BSCS2008
Questions	30
Marks	50
Duration	180 min
MCQ	16
Numerical	7
MSQ	7
Official paper	IIT M DIPLOMA AN EXAM QDD3 13 Apr 2025
Negative marking	No negative marking.
Updated	25 Sept 2026

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