MLF End Term: 30 April 2023, Set QPD1-S1 (January 2023 term)

Select all that apply.

1. A

   In Regression, the output variable must be of continuous nature or real value but In Classification, the output variable is categorical.

2. B

   In Regression, we try to find the best fit line, which can predict the output more accurately but In Classification, we try to find the decision boundary, which can divide the dataset into different classes.

3. C

   The Classification Algorithm can be further divided into Linear and Non-linear classifier and the regression algorithms can be divided into Binary regression and Multi-class regression.

4. D

   Regression algorithms can be used to solve the regression problems such as Weather Prediction, House price prediction, etc and Classification Algorithms can be used to solve classification problems such as Identification of spam emails, Speech Recognition, Identification of cancer cells, etc.

Select all that apply.

1. A

2. B

3. C

4. D

Select all that apply.

1. A

   If the columns of A are linearly independent, then Ax = b has exactly one solution for every b.

2. B

   If the columns of A are linearly independent and if the solution for Ax = b exists, then it is unique.

3. C

   If Ax = b has a unique solution, then A is a square matrix.

4. D

   If the columns of a matrix A are linearly dependent, then Ax = 0 has a nontrivial solution.