---------- Forwarded message ---------- From: Aakash Basu <aakash.spark....@gmail.com> Date: Thu, Aug 25, 2016 at 10:06 PM Subject: Need some help To: user@spark.apache.org
Hi all, Aakash here, need a little help in KMeans clustering. This is needed to be done: "Implement Kmeans Clustering Algorithm without using the libraries of Spark. You're given a txt file with object ids and features from which you have to use the features as your data points. This will be a part of the code itself" PFA the file with ObjectIDs and features. Now how to go ahead and work on it? Thanks, Aakash.
clueweb12-0000tw-00-03428 0.819039 -0.40844217 0.1208266 0.082789585 -0.2421226 -0.1707348 -0.38008857 0.1938118 -0.217733 -0.11316321 0.22536139 0.4077712 0.5106064 0.0691058 0.10968939 -0.2776644 -0.5323738 -0.117045596 0.23160939 0.0968846 -6.479684 0.280832 0.1053532 0.258626 -0.1394934 -0.04401499 -0.06274801 0.2977866 0.23100719 -0.1442094 -0.1190624 -0.018465001 -0.5228338 -0.090049796 0.23440179 0.4241498 -0.41945544 -0.37678298 -0.085718594 0.0114066005 -0.11727621 -0.283434 0.368738 0.2701438 -0.2666412 -0.1634044 0.2432622 0.49877137 0.3270268 -0.7572574 clueweb12-0000tw-00-03680 -0.063763246 0.060122482 0.25039256 -0.17695262 -0.024269182 -0.060460586 -0.020093922 -0.28145245 -0.119478844 -0.22801346 -0.0019172033 0.10361874 -0.22672825 -0.17311707 0.18358645 0.07715805 -0.14939435 -0.19412045 -0.034667462 -0.044996627 -5.5738134 0.11706767 0.1936782 -0.027793365 -0.22054577 0.16990958 -0.03664338 0.3563341 0.030425504 0.15397832 0.015848804 0.18880104 0.15031552 0.0662723 0.06305552 0.017769573 0.099713035 -0.05385251 0.086493894 0.055057835 0.106260784 -0.066389546 -0.13271035 -0.11731695 -0.12733212 -0.16161665 -0.13481794 0.14648221 0.041699838 -0.06707647 clueweb12-0000tw-00-04733 -0.30487683 0.37906706 0.092391066 -0.12356548 0.041434832 0.053371474 -0.061796933 -0.34376934 -0.15945148 0.121789776 0.05491904 0.07184038 -0.13218853 -0.26488 0.09069567 0.18619555 -0.20166355 -0.42629552 0.04779238 0.07399226 -6.007872 -0.10489178 0.058998298 0.031324565 -0.045885365 -0.3257782 -0.058766462 0.04142299 -0.024721975 0.15923695 0.012377773 -0.030803397 0.19786847 0.21469156 -0.16236338 -0.13572672 0.1979717 0.010117755 0.21812446 9.308494E-4 0.11536124 -0.044362586 -0.2429856 -0.1789137 0.074494615 0.0022599115 -0.06896331 0.060051132 -0.16935208 0.05135853 clueweb12-0000tw-00-05462 -0.1689229 0.044400293 0.074416816 0.16745372 -0.047404937 -0.07548128 -0.16308217 -0.04896295 0.09722823 -0.06403786 0.04868864 0.012745747 0.01701884 -0.20373678 0.14389461 0.012322425 -0.1292581 -0.08012425 0.12841988 -0.033620425 -5.7025776 0.054090414 0.14100702 0.0735518 -0.055296857 0.121764086 -0.01585382 -0.19469371 0.056806263 0.16898213 -0.13701764 -0.06280311 0.119968586 -0.0025512849 6.280605E-4 0.12848213 0.10212754 -0.023070885 0.13707727 -0.13853486 0.21509309 -0.016114214 0.10025307 0.041132428 -0.11974216 -0.12352202 0.1947182 0.13712671 -0.11699053 0.16696283 clueweb12-0000tw-00-06191 0.05369992 -0.08874621 0.22850059 -0.1836124 -0.117735796 -0.27074137 -0.047539733 0.042012293 0.09973079 0.031871755 0.0653635 0.052989103 -0.121807896 -4.6803567E-4 0.2528799 -0.096173055 -0.07769931 -0.06987546 0.14199859 -0.17673229 -5.7380853 -0.028545447 0.3338006 0.13075967 0.13761607 -0.034920916 -0.060133602 0.22424728 -0.39989826 0.057518493 -0.04785612 0.09987477 0.26938933 0.016046084 -0.15992445 -0.18638565 0.05115415 -0.16499878 0.0066496585 -0.042277105 0.14138252 0.06549572 0.015083913 -0.16352524 0.09245014 -0.04816438 0.17806058 0.16417544 -0.16822924 -0.074308924
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