Qus : 9
WB JECA MCA PYQ
1
What is the key difference between supervised and unsupervised learning?
1
Supervised learning requires labeled data, while unsupervised learning does not. 2
Supervised learning predicts labels, while unsupervised learning discovers patterns. 3
Supervised learning is used for classification, while unsupervised learning is used for regression. 4
Supervised learning is always more accurate than unsupervised learning. Go to Discussion
WB JECA MCA Previous Year PYQ
WB JECA MCA JECA MCA 2025 PYQ
Solution Main difference is presence of labeled data.
Qus : 10
WB JECA MCA PYQ
1
In SVMs, the margin is defined as
1
The perpendicular distance from the decision boundary to the closest support vector. 2
The Euclidean distance between the two farthest data points in the dataset. 3
The difference in predicted probabilities between the two classes. 4
The perpendicular distance from any point to the hyperplane along the normal vector. Go to Discussion
WB JECA MCA Previous Year PYQ
WB JECA MCA JECA MCA 2025 PYQ
Solution Margin = distance to closest support vector.
Qus : 11
WB JECA MCA PYQ
3
An artificially intelligent car decreases its speed based on its distance from the car in front of it. Which method is used?
(A) Naive Bayes
(B) Decision Tree
(C) Linear Regression
(D) Logistic Regression
1
A 2
B 3
C 4
D Go to Discussion
WB JECA MCA Previous Year PYQ
WB JECA MCA JECA MCA 2024 PYQ
Solution
The car’s speed is a continuous variable that depends on the distance from the car ahead. To model this relation, we need a method for predicting a continuous outcome. Linear Regression is used because it maps distance (input) to speed (output).
Correct Answer: (C) Linear Regression
Qus : 14
WB JECA MCA PYQ
3
What is the purpose of the confusion matrix in machine learning?
1
To visualize the distribution of the data in a dataset 2
To compare the performance of different models 3
To evaluate the performance of a classification model 4
To evaluate the performance of a regression model Go to Discussion
WB JECA MCA Previous Year PYQ
WB JECA MCA JECA MCA 2024 PYQ
Solution
Solution:
- Confusion matrix is used in classification tasks .
- It compares predicted vs actual labels (TP, FP, TN, FN).
Answer = (C) To evaluate the performance of a classification model
Qus : 15
WB JECA MCA PYQ
3
Which of the following is an example of a classification problem?
1
Predicting the price of a house based on its features 2
Predicting the weight of a person based on their height 3
Predicting whether a customer will churn or not 4
Predicting the age of a person based on their income Go to Discussion
WB JECA MCA Previous Year PYQ
WB JECA MCA JECA MCA 2024 PYQ
Solution
Solution: Classification predicts categories . Customer churn = Yes/No ⇒ classification.
Answer: (C) Predicting whether a customer will churn or not
Qus : 16
WB JECA MCA PYQ
1
What is the difference between supervised and unsupervised learning?
1
Supervised learning requires labelled data while unsupervised learning does not. 2
Unsupervised learning requires labelled data while supervised learning does not. 3
Supervised learning does not require data while unsupervised learning does. 4
There is no difference between supervised and unsupervised learning. Go to Discussion
WB JECA MCA Previous Year PYQ
WB JECA MCA JECA MCA 2024 PYQ
Solution
Solution: Supervised = labelled data, Unsupervised = unlabelled data.
Answer: (A) Supervised learning requires labelled data while unsupervised learning does not.
[{"qus_id":"12637","year":"2024"},{"qus_id":"12642","year":"2024"},{"qus_id":"12648","year":"2024"},{"qus_id":"12651","year":"2024"},{"qus_id":"12662","year":"2024"},{"qus_id":"12664","year":"2024"},{"qus_id":"12804","year":"2023"},{"qus_id":"12805","year":"2023"},{"qus_id":"12806","year":"2023"},{"qus_id":"12807","year":"2023"},{"qus_id":"12809","year":"2023"},{"qus_id":"12810","year":"2023"},{"qus_id":"12811","year":"2023"},{"qus_id":"17740","year":"2025"},{"qus_id":"17742","year":"2025"},{"qus_id":"17745","year":"2025"}]