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# CS614 Data Warehousing Assignment No 03 Fall 2020 Solution & Discussion

CS614 Data Warehousing Assignment No 03 Fall 2020 Solution & Discussion

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CS614-Assign#3-solution-fall-2020

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CS614 Assignment No.3 2021

CS614 assignment 3 solution 2021

Aslam u alaikum dear students please download solution file from link which is available at the end of page. Thanks

Question 1(Marks 15)

Classification is a very important method or technique of data mining where the classification model is constructed through the help association rules extracted from the training dataset.

Judge the below training dataset containing the customers’ data of a bank. The column Last_Transaction consists the number of days when active 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 available training dataset which is given below, the following association rules represent for the classification model.

IF Gender is equal (=) Female THEN  Loyalty = YES

ELSE

IF Age is greater than (>)  55 THEN Loyalty = YES

ELSE

IF  Age  is less than (<) 30 THEN Loyalty = NO

ELSE

IF LastTransaction is less than < 60 THEN Loyalty = YES

ELSE Loyalty = NO

Here you will require 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

Note:  You Only require to write YES and NO in the Loyalty column

Question 2 (Marks 05)

Data Mining consists of  two types of learning’s which are  known as supervised learning and un-supervised learning. In the table given some data mining techniques or algorithms are given. You are required to only search and study about them and you require to 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

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