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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>First Steps in Data Mining with Weka - Codepot 2015</title>
<meta name="description" content="A very brief tutorial on using Weka for data analysis and classification.">
<meta name="author" content="Łukasz Kobyliński & Radosław Szmit">
<meta name="apple-mobile-web-app-capable" content="yes" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no, minimal-ui">
<link rel="stylesheet" href="css/reveal.css">
<link rel="stylesheet" href="css/theme/league.css" id="theme">
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</script>
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<script src="lib/js/html5shiv.js"></script>
<![endif]-->
</head>
<body>
<div class="reveal">
<!-- Any section element inside of this container is displayed as a slide -->
<div class="slides">
<section data-background="img/15511720918_194cdcd8a9_o.jpg">
<h1>First steps</h1>
<h1>in Data Mining</h1>
<h1>with Weka</h1>
<hr/>
<h4>Łukasz Kobyliński & Radosław Szmit</h4>
<h4>Codepot 2015</h4>
</section>
<section>
<h2>What is Data Mining?</h2>
<p>Data Mining is a process of discovering hidden information<br/> in data.</p>
<span class="fragment">
<img data-src="img/DIKW_1.png"/>
<p><small>https://visualisingadvocacy.org/blog/disinformation-visualization-how-lie-datavis</small></p></span>
</section>
<section>
<h2>Typical applications</h2>
<h4>Customer analysis</h4>
<img data-src="img/customer_data.png"/>
<ul>
<li>which customers are likely to increase their purchases?</li>
<li>which products are more likely to sell to my customers?</li>
</ul>
</section>
<section>
<section>
<h2>Typical applications</h2>
<h4>Text mining</h4>
<table>
<tr>
<td style="vertical-align: top;">
<ul>
<li>what is the category of this email we have received?</li>
<li>is this product review positive or negative?</li>
<li class="fragment" data-fragment-index="1">what are they saying about me on twitter?</li>
</ul>
</td>
<td><img class="fragment" data-fragment-index="1" data-src="img/sentiment.png"/></td>
</tr></table>
</section>
<section data-background="img/sentiment.png">
</section>
</section>
<section>
<h2>Typical applications</h2>
<h4>Image mining</h4>
<br/>
<table>
<tr>
<td style="vertical-align: top;">
<ul>
<li>which images in my collection contain cats?</li>
<li class="fragment" data-fragment-index="1">which of my contacts are visible on these photos?</li>
<li class="fragment" data-fragment-index="1">what is the sex and age of these people?</li>
</ul>
</td>
<td><img class="fragment" data-fragment-index="1" data-src="img/howoldnet.png"/></td>
</tr></table>
</section>
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<section>
<h2>Data Mining Methods</h2>
<ul>
<li>Regression analysis</li>
<li>Classification</li>
<li>Cluster analysis</li>
<li>Association rule mining</li>
<li>Sequence mining</li>
<li>Anomaly detection</li>
<li>...</li>
</ul>
</section>
<section>
<h2>Task #1</h2>
<h4>Assign names to flowers</h4>
<h4>How do they differ?</h4>
<p><a href="https://www.google.pl/search?q=iris-versicolor&tbm=isch">iris-versicolor</a>,
<a href="https://www.google.pl/search?q=iris-setosa&tbm=isch">iris-setosa</a>,
<a href="https://www.google.pl/search?q=iris-virginica&tbm=isch">iris-virginica</a></p>
<table>
<tr><td>iris-<input type="text"/></td>
<td>iris-<input type="text" /></td>
<td>iris-<input type="text" /></td></tr>
<tr><td>
<img width="300px" data-src="img/Iris-1.jpg" /></td>
<td><img width="300px" data-src="img/Iris-2.jpg" /></td>
<td><img width="300px" data-src="img/Iris-3.jpg" /></td>
</tr></table>
<aside class="notes">
iris-setosa ma niskie wartości dla wszystkich parametrów oprócz sepal-width (szerokie działki korony).
iris-versicolor ma średnie wartości dla wszsytkich parametrów.
iris-virginica ma wysokie wartości dla wszystkich parametrów oprócz sepal-width.
</aside>
</section>
<section>
<section>
<h2>Fisher's iris dataset</h2>
<h4>petals and sepals</h4>
<img width="300px" data-src="img/iris_petal_sepal.png" />
<img width="300px" data-src="img/Petal-sepal.jpg" />
</section>
<section>
<h2>Fisher's iris dataset</h2>
<a href="http://mbostock.github.io/d3/talk/20111116/iris-splom.html">http://mbostock.github.io/d3/talk/20111116/iris-splom.html</a>
<hr/>
<img width="700px" data-src="img/scatterplot.png" />
</section>
</section>
<!-- Weka demo #1 - explore the data -->
<section>
<h2>Task #2</h2>
<h4>Answer the questions:</h4>
<ul>
<li>iris-setosa has:</li>
<ul>
<li>low values of <input type="text"/></li>
<li>high values of <input type="text"/></li>
</ul>
<li>iris-virginica has:</li>
<ul>
<li>low values of <input type="text"/></li>
<li>high values of <input type="text"/></li>
</ul><br/>
<li>the three classes are best separated by:</li>
<ul>
<li>sepallength</li>
<li>sepalwidth</li>
<li>petalwidth</li>
</ul>
</ul>
</section>
<!-- Weka demo #2 - classification -->
<section>
<h2>Task #3</h2>
<h4>Use the <b>rules.PART</b> classifier on the iris dataset and answer the questions:</h4>
<ul>
<li>which is better on this dataset: J48 or PART?</li>
<li>how many examples of iris-versicolor have been classified as iris-setosa?</li>
<li>how many examples of iris-virginica have been classified as iris-versicolor?</li>
<br/>
<li>what is the accuracy of the classifier on the training set?</li>
</ul>
</section>
<!-- Weka demo #3 - visualization -->
<section>
<h2>Task #4</h2>
<h4>Use the J48 classifier on the iris dataset and answer the questions:</h4>
<ul>
<li>use the tree visualization pane to manually perform classification of the following example:</li>
<ul>
<li>sepallength=6.7, sepalwidth=3.0</li>
<li>petallength=5.0, petalwidth=1.7</li>
</ul>
<li>are all the attributes used in the classifier?</li>
<br/>
<li>what are the numbers of instances of type iris-versicolor, which were misclassified as iris-virginica? <br/>(use the Visualize classifier errors panel).</li>
</ul>
</section>
<!-- Weka demo #4 - select attributes, filter and reclassify -->
<!--http://www.thearling.com/text/dmwhite/dmwhite.htm-->
<section>
<section>
<h2>Data: the evolution</h2>
<table>
<tr><td style="background-color: #71FF73">Big Data</td></tr>
<tr><td style="background-color: #CFE848">Data Mining and Knowledge Discovery</td></tr>
<tr><td style="background-color: #FFDD5B">Data Warehousing</td></tr>
<tr><td style="background-color: #E89D48">Data Access</td></tr>
<tr><td style="background-color: #FF6C4F">Data Collection</td></tr>
</table>
</section>
<section>
<h2>Data: the evolution</h2>
<table>
<tr><td style="background-color: #71FF73">Big Data</td></tr>
<tr><td><small>"What’s likely to happen to online sales, considering 1M visits/day?"</small></td></tr>
<tr><td style="background-color: #CFE848">Data Mining and Knowledge Discovery</td></tr>
<tr><td><small>"What’s likely to happen to Boston unit sales next month? Why?"</small></td></tr>
<tr><td style="background-color: #FFDD5B">Data Warehousing</td></tr>
<tr><td><small>"What were unit sales in New England last March? Drill down to Boston."</small></td></tr>
<tr><td style="background-color: #E89D48">Data Access</td></tr>
<tr><td><small>"What were unit sales in New England last March?"</small></td></tr>
<tr><td style="background-color: #FF6C4F">Data Collection</td></tr>
<tr><td><small>"What was my total revenue in the last five years?"</small></td></tr>
</table>
</section>
</section>
<section>
<h1 style="text-align: left;">THE END</h1>
<h4 style="text-align: left;">Thanks!</h4><br/>
<hr/>
<table>
<tr><td>Łukasz Kobyliński</td><td>Radosław Szmit</td></tr></table>
<a href="http://www.sages.com.pl"><img style="border: none; background: none; box-shadow: none;" data-src="img/sages.png" /></a>
<a href="http://www.sages.com.pl">http://www.sages.com.pl</a>
</section>
</div>
</div>
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