Machine Learning 1: UNIT 2: Classification Questions

                                                                                UNIT-II

                                                                        CLASSIFICATION

Long Answer Questions

 

1.     Apply a Binary Classifier for a given dataset and evaluate its performances using Accuracy, Precision, Recall, F1 Score, Precision/Recall Trade-off.

	Not 5	5
Not 5	53057	1522
5	1325	4096

 

2.     Explain kNN Classifier Algorithm with an example.

3.     How can you be measuring accuracy using cross validation? Explain.

4.     Predict the class label for new instance x1=6, x2=8 for the following dataset using kNN Classifier. Explain kNN Algorithm.

X1	X2	Class Label
4	3	F
6	7	P
7	8	P
5	5	F
8	8	P

5.     How can you train a Binary Classifier? Explain with example.

6.     List the different performance metrics? Explain them with example.

7.     What is the confusion matrix? How can you get the confusion matrix?

8.     Define Precision and Recall. How can you get these values?

9.     Explain Precision/Recall Trade-off with example.

10.  What is ROC Curve. What is the importance of ROC Curve?

11.  Explain multiclass classification with example.

12.  How can you perform error analysis? Explain.

13.  Explain Multilabel Classification with example.

 

14.  Explain Multioutput Classification with example.