Mahdi Dibaiee
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85971bc84d
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feat(w2v): draw text charts for words
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2016-10-01 12:24:36 +03:30 |
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Mahdi Dibaiee
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d9d24f69a6
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feat(blogs-corpus): new corpus for word2vec
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2016-09-19 16:00:45 +04:30 |
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Mahdi Dibaiee
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f16cc26798
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perf(word2vec): better word2vec
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2016-09-16 18:46:21 +04:30 |
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Mahdi Dibaiee
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0d43814448
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fix(word2vec): simple example of word2vec
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2016-09-16 14:03:15 +04:30 |
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Mahdi Dibaiee
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d4ac90bbd5
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rm(sin): remove sin example
fix(ignoreBiases): was ignoring nodes, lol
fix(w2v): better logging and implementation
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2016-09-16 13:31:23 +04:30 |
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Mahdi Dibaiee
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c0083f5c05
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fix(notmnist): notmnist sigmoid chart with 10 epochs
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2016-09-13 10:04:30 +04:30 |
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Mahdi Dibaiee
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6b9cb1fa3e
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relu: run notmnist using relu activation and draw the chart
[wip] word2vec: work in progress implementation of word2vec
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2016-09-13 09:49:44 +04:30 |
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Mahdi Dibaiee
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b26347e19f
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feat(notmnist): notmnist example using SGD + learning rate decay
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2016-09-10 00:36:15 +04:30 |
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Mahdi Dibaiee
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891f48a2d0
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feat(topten): top-ten classification with evenly distrubuted data
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2016-08-21 00:59:42 +04:30 |
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Mahdi Dibaiee
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b2888417bb
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fix(cleanText): remove unnecessary spaces
fix(run): use `1 - prior` for alpha, no need for smoothing
feat(cleanText): turn all text to lowercase
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2016-08-09 16:04:57 +04:30 |
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Mahdi Dibaiee
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eebf5e0222
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feat(verbose): print more information using -v or --verbose flags
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2016-08-08 12:35:26 +04:30 |
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Mahdi Dibaiee
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099c25e166
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feat(stopwords): removeWords and removeStopwords functions as pre-processors
feat(confidence, WIP): calculate confidence of each classification
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2016-08-08 10:02:26 +04:30 |
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Mahdi Dibaiee
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ea1f05f001
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fix(naivebayes): fix the algorithm to make it actually work
feat(cleanDocuments): preprocess documents, use stemming and stopword elimination for better accuracy
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2016-08-05 23:54:36 +04:30 |
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Mahdi Dibaiee
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3cf0625794
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fix(precision): little bug in implementation
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2016-07-30 16:52:34 +04:30 |
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Mahdi Dibaiee
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76e7e7faef
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fix(recall, precision): little bug in calculations
feat(fmeasure): calculate fmeasure using recall and precision
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2016-07-29 22:09:30 +04:30 |
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Mahdi Dibaiee
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812717522e
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refactor(&&&): use &&& instead of the arrow function
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2016-07-29 18:20:35 +04:30 |
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Mahdi Dibaiee
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b5b4629318
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feat(results): accuracy, recall and precision functions used to calculate measures
fix: read data from another repository
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2016-07-29 17:55:59 +04:30 |
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Mahdi Dibaiee
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26eb4531fa
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feat(naivebayes): implement NaiveBayes algorithm
feat(example): a document classifier using NaiveBayes over reuters data
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2016-07-29 16:16:44 +04:30 |
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