Semester Fall 2020
Data Warehousing– CS614 Total Marks: 20
Due Date: 01-02-2021
Question 1 (Marks 15)
Classification is an important technique of data mining where the classification model is constructed through association rules extracted from the training dataset.
Consider the following training dataset containing the customers’ data of a bank. The column Last_Transaction contains the number of days when customers have made their last transactions.
Gender Age Last_Transaction Loyalty
Male 64 98 YES
Male 35 125 NO
Female 25 50 YES
Male 39 50 YES
Male 45 90 NO
Female 42 165 YES
Male 21 25 NO
Male 48 28 YES
Female 55 110 YES
Male 58 120 YES
On the basis of the given training dataset, the following association rules constitute for the classification model.
IF Gender = Female THEN Loyalty = YES
IF Age > 55 THEN Loyalty = YES
IF Age < 30 THEN Loyalty = NO
IF LastTransaction < 60 THEN Loyalty = YES
ELSE Loyalty = NO
You are required to identify the class for the following customers.
Gender Age Last Transaction Loyalty
Male 20 15 No
Male 49 41 No
Male 68 75 Yes
Female 29 128 Yes
Male 53 85 Yes
Question 2 (Marks 05)
Data Mining contains two types of learning which are called supervised learning and un-supervised learning. In the following table some data mining techniques/algorithms are given. You are required to search and study about them and identify their proper type.
Sr No. Techniques/Algorithms Type (Supervised/Un-supervised)
1 Classification Supervised
2 Support Vector Machine (SVM) Supervised
3 Regression Supervised
4 K-means Supervised
5 K- nearest neighbor (K-NN) Supervised
CS614 – Data Warehousing-Assignment-3 Solution