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IIT M DIPLOMA QUIZ2 EXAM QPF1 10 July 2022 - 10 Jul 2022

MLP Quiz 222 questions50 marks17 MCQ · 4 SA · 1 MSQDiploma / QUIZ2

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Q1MCQ0 marks

Q2MCQ1 mark

Which of the following vectorizer techniques can help to convert a large collection of text documents to a matrix?

CountVectorizer
HashingVectorizer
Both CountVectorizer and HashingVectorizer
None of these

Q3MCQ2 marks

Q4MCQ2 marks

0.0
1.0
-1.0
0.5

Q5MCQ2 marks

Which of the options below represent the correct method to preprocess class labels in multi-class setup?

Q6MCQ2 marks

Q7MCQ2 marks

0.65
0.73
0.37
None of these

Q8MCQ2 marks

Rakesh is solving a regression problem with a KNN model. He has considered k = 3 for his model. Based on the graph shown below, what would you suggest him out of the following options? question figure

Rakesh is solving a regression problem with a KNN model. He has considered k = 3 for his model. Based on the graph shown below, what would you suggest him out of the following options?

His model is suffering from overfitting. So, he should increase the value of k.
His model is suffering from underfitting. So, he should increase the value of k.
His model is suffering from overfitting. So, he should decrease the value of k.
His model is suffering from underfitting. So, he should decrease the value of k.
No suggestions, Rakesh has already chosen the best value of k.

Q9MCQ2 marks

l1 penalty in LinearSVC classifier leads to coef_vectors which are-

dense.
sparse.
Unique class labels.
l1 penalty can’t be set via a parameter in LinearSVC.

Q10MCQ3 marks

1
0
0.5
0.40

Q11MCQ3 marks

Q12MCQ3 marks

The classifier shown in ‘Curve B’ is better than the other two classifiers.
The classifier shown in ‘Curve A’ is better than the other two classifiers.
The classifier shown in ‘Curve C’ is better than the other two classifiers.
All 3 curves demonstrate 3 classifiers of the same quality.

Q13MCQ3 marks

For a text classification task, which one of the following code snippets will be better suitable than the others?

Q14MCQ3 marks

0
1
2
None

Q15MCQ3 marks

Q16MCQ3 marks

Q17MSQ3 marksselect all that apply

Which of the following code blocks will correctly train a large scale regression model using partial_fit, if shape of X_train,Y_train are given as (8000,900,10) and (8000,900) respectively. Note that the dataset has been transformed into batches of size 900 each?