MITS5509 Assignment 3 MITS5509 Intelligent Systems for Analytics Assignment 3 MITS5509 Assignment 3 Copyright © XXXXXXXXXXVIT, All Rights Reserved. 2 NOTE: This Document is used in conjunction with...

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MITS5509 Assignment 3 MITS5509 Intelligent Systems for Analytics Assignment 3 MITS5509 Assignment 3 Copyright © 2015-2018 VIT, All Rights Reserved. 2 NOTE: This Document is used in conjunction with MITS5509 Objective(s) This assessment item relates to the unit learning outcomes as in the unit descriptor. This assessment is designed to improve student collaborative skills in a team environment and to give students experience in constructing a range of documents as deliverables form different stages of the Intelligent Systems for Analytics INSTRUCTIONS Assignment 3 :- Group Assignment (30 %) and submission at week 12 In this assignment students will work in small groups to develop components of the Documents discussed in lectures. Student groups should be formed by Session four. Each group needs to complete the group participation form attached to the end of this document. Assignments will not be graded unless the student has signed a group participation form. Carefully read the following two questions and provide the appropriate answer. Question 1. The bankruptcy-prediction problem can be viewed as a problem of classification. The data set you will be using for this problem includes two ratios that have been computed from the financial statements of real-world firms. These two ratios have been used in studies involving bankruptcy prediction. The first sample (training set) includes 68 data value on firms that went bankrupt and firms that didn't. This will be your training sample. The second sample (testing set) of 68 firms also consists of some bankrupt firms and some non bankrupt firms. Your goal is to use different classifiers to build a training model, by randomly selecting the 40 data points (20 points from category 1 and 20 points from category 0), and then test its performance on the testing model by randomly selecting 40 data points from the testing set. (Try to analyze the new cases yourself manually before you run the neural network and see how well you do). Both Data Sets are provided below: Students have to use the following classifiers. The selection of the classifiers depend upon the members of the group. E.g. If the group has four members then they will use the four classifiers from the following six classifiers. 1. Neural networks 2. Support vector machines 3. Nearest neighbor algorithms 4. Decision trees 5. Naive Bayes 6. Any other classifier MITS5509 Assignment 3 Copyright © 2015-2018 VIT, All Rights Reserved. 3 The following tables show the training sample and test data you should use for this exercise. Training set Firm WC DC Category 1 3338.61 0.56555 1 2 3801.72 0.570567 1 3 2818.817 0.572058 1 4 1250.953 0.568258 1 5 2444.406 0.553276 1 6 937.917 0.561066 1 7 1600.792 0.534662 1 8 3128.813 0.564714 1 9 2486.803 0.564239 1 10 4220.996 0.58465 1 11 2585.41 0.572457 1 12 3512.085 0.550878 1 13 4170.333 0.569516 1 14 938.879 0.545574 1 15 1437.695 0.529922 1 16 627.985 0.51941 1 17 4430.049 0.567547 1 18 989.568 0.534501 1 19 3275.474 0.555306 1 20 1500.437 0.565886 1 21 848.989 0.548603 1 22 1386.494 0.56229 1 23 1554.257 0.562346 1 24 2228.338 0.565556 1 25 2568.391 0.54973 1 26 1720.128 0.568458 1 27 4106.106 0.57767 1 28 3500.883 0.557197 1 29 1217.846 0.525333 1 30 3544.406 0.568735 1 31 2082.873 0.557527 1 32 709.01 0.541673 1 33 2523.939 0.55366 1 34 2781.307 0.569188 1 35 309.577 0.557668 0 36 363.79 0.561751 0 37 341.399 0.550717 0 38 363.616 0.568882 0 MITS5509 Assignment 3 Copyright © 2015-2018 VIT, All Rights Reserved. 4 39 323.673 0.554499 0 40 323.353 0.558233 0 41 350.371 0.566447 0 42 240.602 0.5656 0 43 220.057 0.544182 0 44 287.837 0.522119 0 45 274.6 0.551492 0 46 278.494 0.550846 0 47 234.267 0.554828 0 48 284.923 0.533586 0 49 190.62 0.54899 0 50 327.76 0.538896 0 51 211.94 0.551569 0 52 373.571 0.549753 0 53 219.891 0.546936 0 54 193.489 0.56059 0 55 204.333 0.550777 0 56 205.657 0.550677 0 57 362.361 0.551315 0 58 285.562 0.578965 0 59 352.649 0.541763 0 60 400.44 0.557809 0 61 307.301 0.578949 0 62 240.314 0.548355 0 63 322.995 0.569978 0 64 408.197 0.574972 0 65 209.027 0.554203 0 66 198.979 0.559771 0 67 340.418 0.57343 0 68 320.154 0.560661 0 MITS5509 Assignment 3 Copyright © 2015-2018 VIT, All Rights Reserved. 5 Testing set Firm WC DC 1 4204.066 0.578231 2 1411.733 0.560415 3 4197.206 0.565368 4 1121.866 0.540554 5 820.683 0.566067 6 1349.887 0.524683 7 3128.736 0.547596 8 2551.433 0.57368 9 809.115 0.552148 10 2866.623 0.559484 11 1193.951 0.515996 12 2014.445 0.564598 13 4400.268 0.578645 14 266.396 0.550131 15 243.554 0.559966 16 172.184 0.566274 17 362.479 0.553563 18 249.981 0.55274 19 327.877 0.565451 20 286.696 0.572919 21 182.762 0.56313 22 338.347 0.546618 23 302.57 0.551846 24 1781.718 0.564307 25 3711.358 0.570857 26 2030.189 0.564332 27 845.019 0.550468 28 1925.183 0.574114 29 1549.089 0.538726 30 1953.371 0.577015 31 932.5 0.564721 32 924.554 0.554162 33 2386.011 0.545268 34 2112.875 0.560262 35 3568.877 0.561775 36 4104.984 0.570978 37 367.325 0.533232 38 347.513 0.552354 39 330.226 0.549799 MITS5509 Assignment 3 Copyright © 2015-2018 VIT, All Rights Reserved. 6 40 178.106 0.574406 41 378.899 0.531441 42 257.212 0.565379 43 333.088 0.54545 44 182.324 0.569686 45 238.099 0.563344 46 329.643 0.558005 47 294.644 0.556574 48 1058.649 0.54729 49 956.021 0.546774 50 2089.824 0.572031 51 2198.033 0.558597 52 4538.527 0.560383 53 3137.934 0.544445 54 2002.459 0.58141 55 2136.376 0.562953 56 281.666 0.553904 57 308.086 0.553646 58 317.079 0.560538 59 245.139 0.567829 60 354.662 0.548939 61 292.256 0.557991 62 306.79 0.57065 63 222.396 0.547811 64 367.628 0.53711 65 342.115 0.562531 66 353.326 0.548094 67 336.39 0.539131 68 298.008 0.562856 From the above data set, the group has to prepare a report which include the following: 1. List the values (40 values) in the Table used for Training set 2. List the values (40 values) in the Table used for Testing set 3. The output results of each classifier for the testing set in Table form 4. Snapshot or Screenshot of each of the steps Note: Students can use any open source free data mining software such as Statistica Data Miner, Weka, RapidMiner, KNIME and MATLAB etc. MITS5509 Assignment 3 Copyright © 2015-2018 VIT, All Rights Reserved. 7 Question 2. Create a DASHBOARD. For creating a dashboard, the group can use the above database or any other database. The group have to prepare a report which include the following: 1. List of the values in the Table used for creating the dashboard 2. A Snapshot or Screenshot of each of the steps The above list of documents is not necessarily in any order. The chronological order we cover these topics in lectures is not meant to dictate the order in which you collate these into one coherent document for your assignment. Your report must include a Title Page with the title of the Assignment and the name and ID numbers of all group members. A contents page showing page numbers and titles of all major sections of the report. All Figures included must have captions and Figure numbers and be referenced within the document. Captions for figures placed below the figure, captions for tables placed above the table. Include a footer with the page number. Your report should use 1.5 spacing with a 12 point Times New Roman font. Include references where appropriate. Citation of sources (if using any ) is mandatory and must be in the Harvard style. Only one submission is to be made per group. The group should select a member to submit the assignment by the due date and time. All members of the group will receive the same grade unless special arrangement is made due to group conflicts. Any conflict should be resolved by the group, but failing that, please contact your lecture who will then resolve any issues which may involve specific assignment of work tasks, or removal of group members. What to Submit All submissions are to be submitted through turn-it-in. Drop-boxes linked to turn-it-in will be set up in the Unit of Study Moodle account. Assignments not submitted through these drop-boxes will not be considered. Submissions must be made by the due date and time (which will be in the session detailed above) and determined by your Unit coordinator. Submissions made after the due date and time will be penalized at the rate of 10% per day (including weekend days). The turn-it-in similarity score will be used in determining the level if any of plagiarism. Turn-it-in will check conference web-sites, Journal articles