<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Topics tagged with cs725]]></title><description><![CDATA[A list of topics that have been tagged with cs725]]></description><link>https://community.secnto.com//tags/cs725</link><generator>RSS for Node</generator><lastBuildDate>Mon, 08 Jun 2026 20:47:41 GMT</lastBuildDate><atom:link href="https://community.secnto.com//tags/cs725.rss" rel="self" type="application/rss+xml"/><pubDate>Invalid Date</pubDate><ttl>60</ttl><item><title><![CDATA[CS725 Assignment 4 Solution and Discussion]]></title><description><![CDATA[<p dir="auto">CS725 Assignment 4 Solution and Discussion</p>
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Question# 01
Solution: (30pts)
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Data Mining (CS725)<br />
Assignment # 01 Total Points: 50<br />
Please read the instructions before stepping in to the assignment solution. Please try to complete and upload your assignment on or before due date. No assignment will be considered after due date through email.<br />
Instructions:<br />
Please apply/ perform all the steps.<br />
Copying from other students or any other source will be<br />
marked as ZERO.<br />
Screenshots of assignment solution will not be considered.<br />
Assignment solution must be typed.<br />
Screenshots of Mathematical Equation will lead to marks deduction.<br />
No assignment will be entertained through email.<br />
Be specific and to the point in assignment solution. No assignment after due date will be accepted.<br />
Due Date: January 16th, 2020<br />
1</p>
<p dir="auto">Fall 2019 Data Mining<br />
Virtual university of Pakistan<br />
Question# 01<br />
Consider the following dataset mentioned below:<br />
(10pts)</p>
<table class="table table-bordered table-striped">
<thead>
<tr>
<th>Actual</th>
<th colspan="2">Predicted</th>
</tr>
</thead>
<tbody>
<tr>
<td colspan="2"></td>
<td>Yes</td>
<td>No</td>
</tr>
<tr>
<td></td>
<td>Yes</td>
<td>70</td>
<td>30</td>
</tr>
<tr>
<td>No</td>
<td>40</td>
<td>60</td>
</tr>
</tbody>
</table>
<p dir="auto">Now calculate the following:<br />
i. Sensitivity<br />
ii. Specificity<br />
iii. Error rate<br />
Question# 02<br />
(40pts)<br />
Consider the following class-labeled training tuples from the weather forecast dataset mentioned below:<br />
<img src="https://i.imgur.com/1b7fEUu.png" alt="6b04fe2a-ba86-4ad9-a428-96fc0eaacd25-image.png" class=" img-fluid img-markdown" /></p>
<p dir="auto">a) Calculate the Gain for every mentioned attribute and identify which attribute will be chosen for splitting?<br />
b) Compute the Gini index for the overall collection of training dataset</p>
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