Model Question Paper-1
Machine Learning
VI Sem BCA
PART-A
I. Answer any Four questions, each carries Two marks. (4x2=8)
1) What is Data Cleaning?
2) What is Regression?
3) Define Data preparation.
4) What is Classification?
5) Write the types of unsupervised learning.
6) What is Clustering?
PART-B
II. Answer any Four questions, each carries Five marks. ( 4 x 5 = 20 )
7) Explain the types of machine learning.
8) Explain K-NN algorithm.
9) Explain Clustering methods.
10) Write the steps of machine learning process.
11) Explain five exploratory data analysis methods.
12) List the types of Pruning and explain.
PART C
III. Answer any Four questions, each carries Five marks. ( 4 x 8 = 32 )
13) What are types of machine learning system?
14) Explain data cleaning.
14) Explain performance metrics.
15) Explain K-means clustering.
16) Explain Machine Learning techniques.
17) Explain Data preparation.
18) Explain Decision tree.
Model Question Paper-2
Machine Learning
VI Sem BCA
PART-A
I. Answer any Four questions, each carries Two marks. (4x2=8)
1) Define machine learning?
2) Define dataset.
3) What is data splitting?
4) Write 2 tools used for Machine learning.
5) Define Data Splitting.
6) What are differences between classification and regression?
PART-B
II. Answer any Four questions, each carries Five marks. ( 4 x 5 = 20 )
7) Explain Bayes theorem.
8) Explain Scikit technique..
9) Discuss the difference b/w supervised learning and unsupervised learning.
10) Explain exploratory data analysis.
11) Write the challenges of machine learning model.
12) Explain K-means clustering with Image segmentation.
PART C
III. Answer any Four questions, each carries Five marks. ( 4 x 8 = 32 )
13) What are pandas and sci-kit?
14)Explain DBSCAN algorithm.
14). Explain decision tree algorithm.
15) Explain confusion matrix.
16) Explain unsupervised techniques.
17) Explain Partitioning Clustering.
18) Explain Regression models.
