The following code snippet shows the use of two models built on the data X and label y: import numpy as np from sklearn.preprocessing import MinMaxScaler from sklearn.neighbors import KNeighborsClassifier from sklearn.pipeline import Pipeline X = np.array([[0, 0], [0.25, 0.25], [0.5, 0.5], [0.75, 0.75], [1, 1]]) y = np.array([0, 0, 1, 1, 0]) model_1 = Pipeline([ ('knn', KNeighborsClassifier(n_neighbors=3)) ]) model_2 = Pipeline([ ('scaler', MinMaxScaler()), ('knn', KNeighborsClassifier(n_neighbors=3)) ]) model_1.fit(X, y) model_2.fit(X, y) For the given data, which of the following options is correct?

(C) Option figure from the original question paper

(A) Option figure from the original question paper

(B) Option figure from the original question paper

(D) Option figure from the original question paper

Machine Learning Practice · End Term · 13 Apr 2025 · January 2025 term · Set QDD1

Question 11: The following code snippet shows the use of two models b…

Question 11

+2 marksOne correct option

The following code snippet shows the use of two models built on the data $X$ and label $y$ :

python

1import numpy as np
2from sklearn.preprocessing import MinMaxScaler
3from sklearn.neighbors import KNeighborsClassifier
4from sklearn.pipeline import Pipeline
5
6X = np.array([[0, 0], [0.25, 0.25], [0.5, 0.5], [0.75, 0.75], [1, 1]])
7y = np.array([0, 0, 1, 1, 0])
8
9model_1 = Pipeline([
10    ('knn', KNeighborsClassifier(n_neighbors=3))
11])
12
13model_2 = Pipeline([
14    ('scaler', MinMaxScaler()),
15    ('knn', KNeighborsClassifier(n_neighbors=3))
16])
17
18model_1.fit(X, y)
19model_2.fit(X, y)

For the given data, which of the following options is correct?

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Question 11 of 30 in the IIT Madras BS Machine Learning Practice (MLP) End Term paper sat on 13 Apr 2025, in the January 2025 term (IIT M DIPLOMA AN EXAM QDD3 13 Apr 2025). It carries 2 marks.

Question 11: The following code snippet shows the use of two models b…

Question 11

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