<NME> ExpIndex.txt
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+  1: regression data set memory usage test
+  2: check manually extracted ngrams
+  3: single label feature extraction using elasticsearch,
+  4: single label feature sampling gradient boosting
+  5: build cnn index
+  6: check purity of features
+  7: dump data set info for exp3
+  8: index Ohsumed_20000
+  9: merge 20nesgroup into 8 classes
+  10: ecoc
+  11: for single label dataset, dump unigram features
+  12: for multi label dataset, dump unigram features
+  13: hmlgb
+  14: imlgb
+  15: feature extraction for multi label dataset
+  16: index review polarity
+  17: index classic3
+  18:  single label dataset, start with initial features + all unigram features
+       use picked unigram features as seeds
+  19: single label gradient boosting without probabilistic voting
+  20: single label lasso
+  21: single label ridge
+  22: elastic net hyper parameter tuning, single label
+  23: index 20newsgroup
+  24: index imdb
+  25: elastic net, single label
+  26: gradient boosting hyper parameter tuning, single label
+  27: lasso hyper parameter tuning
+  28: ridge hyper parameter tuning
+  29: index imdb_stopwords
+  30: given logistic regression coefficients, print top features
+  31: feature extraction by logistic regression, see 37
+  32: given feature indices, get feature names
+  33: logistic regression
+  34: logistic regression hyper parameter tuning via cross validation
+  35: dump unigram features
+      split to train/valid/test
+  36: logistic regression hyper parameter tuning with validation set
+  37: feature extraction by logistic regression, with train/valid/test split
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make ExpIndex a txt file