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  "fetched_at": "2026-10-23T03:32:54Z",
  "source_url": "https://www.kaggle.com/competitions/ece657aw21-assignment1-iris-dataset/data",
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      "name": "data-description",
      "content": "<p>The Iris flower data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper. The data set consists of 50 samples from each of three species of Iris (Iris Setosa, Iris virginica, and Iris versicolor). Four features were measured from each sample: the length and the width of the sepals and petals, in centimeters.</p>\n<h2> Feature descriptions</h2>\nThe columns in this dataset are:\n<ul>\n<li> Id</li>\n<li> SepalLengthCm</li>\n<li> SepalWidthCm</li>\n<li> PetalLengthCm</li>\n<li> PetalWidthCm</li>\n<li> Species</li>\n</ul>",
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      "content": "\n<p>Assignment 1 aims at setting up the basic programming environment (python) and use the <b>Iris dataset</b> and the <b>Heart Disease</b> datasets to answer the assignment questions.</p>\n<ul>\n<li><b>Dataset 1:</b> - Irish Dataset, this kaggle - <a href=\"https://www.kaggle.com/c/ece657aw21-assignment1\">https://www.kaggle.com/c/ece657aw21-assignment1</a>\n</li><li><b>Dataset 2:</b> - Heart Disease Dataset, kaggle link - <a href=\"https://www.kaggle.com/c/ece657aw21-assignment1-heartdisease\">https://www.kaggle.com/c/ece657aw21-assignment1-heartdisease</a>\n</li></ul>\n\n<h2>Due Date:  3rd February 2021</h2>\n\n\n<h2>Specific objectives</h2>\n<ul><li> Establish your software stack to carry out data analysis\nassignments for the rest of the course.</li>\n  <li>Load datasets and perform some exploratory plots.</li>\n  <li>Study how to apply some of the methods discussed in class and gain experience on the use of this classification methods.</li>\n</ul>\n<h2>Tools</h2> \n<p>You can use libraries available in python. You need to mention which\nlibraries you are using, any blogs or papers you used to figure out how to carry out your\ncalculations.</p>\n<h2>Collaboration:</h2>\n<p> You may do your work individually or in pairs. You can collaborate with other on the right tools to use and setting up your programming environment. Both members of the pair must sign up for a PairGroup in LEARN. </p>\n\n<hr>\n\n<h2>Dataset 2: Iris Dataset</h2>\nThis dataset comes from the UCI Machine Learning Repository:  <a href=\"https://archive.ics.uci.edu/ml/datasets/iris\">Iris Dataset</a>",
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    {
      "name": "Evaluation",
      "content": "<p>The evaluation pages describes how submissions will be scored and how students should format their submissions. You don't need a sub-title at the top (the page title appears above). For an example of a high quality evaluation page, see the 2013 KDD Cup page, which we have copied here:</p>\n<hr>\n<p>The evaluation metric for this competition is <a href=\"https://www.kaggle.com/wiki/MeanFScore\"> Mean F1-Score</a>. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:</p>\n<p>\\[ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} \\]</p>\n<p>The F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.</p>\n<h2>Submission Format</h2>\n<p><strong>For every author in the dataset</strong>, submission files should contain two columns: AuthorId and DuplicateAuthorIds. DuplicateAuthorIds should be a space-delimited list. Every AuthorId counts as his/her own duplicate, and every duplicate should be listed under each of its respective ids.&nbsp;For example, if you suspect author A, B, and C are the same, you should list (A,A B C), (B,B A C), (C,C A B).</p>\n<p>The file should contain a header and have the following format:</p>\n<pre>AuthorId,DuplicateAuthorIds<br>1,1<br></pre>",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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