You are training a Multi-Layer Perceptron (MLP) using Scikit-Learn's MLPRegressor for a regression task. Consider the following code: from sklearn.neural_network import MLPRegressor from sklearn.datasets import make_regression from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler X, y = make_regression(n_samples=1000, n_features=20, noise=0.1, random_state=42) X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) scaler = StandardScaler() X_train = scaler.fit_transform(X_train) X_test = scaler.transform(X_test) model = model.fit(X_train, y_train) Which of the following can be placed in the blank portion (Select all that apply)?

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Machine Learning Practice · End Term · 13 Apr 2025 · January 2025 term · Set QDD3

Question 22: You are training a Multi-Layer Perceptron (MLP) using Sc…

Question 22

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You are training a Multi-Layer Perceptron (MLP) using Scikit-Learn's MLPRegressor for a regression task.

Consider the following code:

python

1from sklearn.neural_network import MLPRegressor
2from sklearn.datasets import make_regression
3from sklearn.model_selection import train_test_split
4from sklearn.preprocessing import StandardScaler
5
6
7X, y = make_regression(n_samples=1000, n_features=20, noise=0.1, random_state=42)
8
9
10X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
11
12scaler = StandardScaler()
13X_train = scaler.fit_transform(X_train)
14X_test = scaler.transform(X_test)
15
16
17model = ________________________
18model.fit(X_train, y_train)

Which of the following can be placed in the blank portion (Select all that apply)?

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Question 22 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 1 mark.

Question 22: You are training a Multi-Layer Perceptron (MLP) using Sc…

Question 22

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