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elbamos / largeVis

An implementation of the largeVis algorithm for visualizing large, high-dimensional datasets, for R
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Dimensionality reduction clumps all but one point together #31

Closed spamcatcher345 closed 7 years ago

spamcatcher345 commented 7 years ago

Apologies for the cross-post, as this issue was reported here also: https://github.com/lferry007/LargeVis/issues/8

Hoping to get some additional visibility.

I have the same issue using Ubuntu 15.10. Has anyone solved this yet? After running Largevis on my dataset, the first point is orders of magnitude larger than the remaining points after dimensionality reduction, resulting in a meaningless plot. root@blah-VirtualBox:/home/blah/Desktop/LargeVis/20161012# ./LargeVis -input 1k_points.txt -output 1k_2d.txt Reading input file 1k_points.txt ...... Done. Total vertices : 1000 Dimension : 64 Normalizing ...... Done. Running ANNOY ...... Done. Running propagation 3/3 Test knn accuracy : 95.98% Computing similarities ...... Done. Fitting model Alpha: 0.000100 Progress: 99.993% root@blah-VirtualBox:/home/blah/Desktop/LargeVis/20161012# root@blah-VirtualBox:/home/blah/Desktop/LargeVis/20161012# head 1k_2d.txt 1000 2 -31.457289 -0.287726 12.466423 -0.287530 12.466411 -0.287530 12.466626 -0.287530 12.466501 -0.287530 12.466530 -0.287530 12.466509 -0.287530 12.466496 -0.287530 12.466705 -0.287530 Here is a link to the input data: https://www.dropbox.com/s/bvup56przujg52d/1k_points.txt?dl=0 And a link to the Largevis output: https://www.dropbox.com/s/jk2p0qof2sn7hr9/1k_2d.txt?dl=0 Any guidance would be greatly appreciated. Thank you!
elbamos commented 7 years ago

I've responded in the other thread, so I'm closing this. The issue appears to have been with your data file. If anything else comes up, please reopen. Thanks.

spamcatcher345 commented 7 years ago

Replied on the other thread. Many thanks again.