tteofili commented on issue #544: LUCENE-5698 - added test for 20n dataset, minor code adjustments URL: https://github.com/apache/lucene-solr/pull/544#issuecomment-455702696 Sample output below: Indexing 20 Newsgroups... Indexed 18756 pages in 10s Splitting the index... Splitting done in 4s Starting evaluation on 3758 docs... * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=1, query=null, similarity=ClassicSimilarity} * accuracy = 0.5645952575633688 * precision = 0.7193188060049855 * recall = 0.716985815879549 * f1-measure = 0.7181504162039081 * avgClassificationTime = 79.10138371474189 * time = 297 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=1, query=null, similarity=BM25(k1=1.2,b=0.75)} * accuracy = 0.6007493755203996 * precision = 0.7494545012936403 * recall = 0.7448586882811808 * f1-measure = 0.7471495274947597 * avgClassificationTime = 17.038584353379456 * time = 64 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=ClassicSimilarity} * accuracy = 0.5658217497955846 * precision = 0.719843869712185 * recall = 0.7171801181044266 * f1-measure = 0.7185095250655141 * avgClassificationTime = 79.05321979776477 * time = 297 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=F1EXP} * accuracy = 0.5808853951179148 * precision = 0.7326340623733987 * recall = 0.72991764555491 * f1-measure = 0.7312733313455378 * avgClassificationTime = 36.88983501862693 * time = 139 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=F1LOG} * accuracy = 0.587979274611399 * precision = 0.7384996344849235 * recall = 0.7347149186935997 * f1-measure = 0.7366024150863697 * avgClassificationTime = 27.64129856306546 * time = 104 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=LM Dirichlet(2000.000000)} * accuracy = 0.7483885307846188 * precision = 0.8495917468705413 * recall = 0.8474232077825243 * f1-measure = 0.848506091787247 * avgClassificationTime = 52.95769026077701 * time = 199 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=LM Jelinek-Mercer(0.300000)} * accuracy = 0.774876181900045 * precision = 0.8653964266094933 * recall = 0.8645520449551223 * f1-measure = 0.8649740297124768 * avgClassificationTime = 50.552421500798296 * time = 190 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=BM25(k1=1.2,b=0.75)} * accuracy = 0.7695769576957696 * precision = 0.8627976686889449 * recall = 0.8614099411930625 * f1-measure = 0.8621032464851681 * avgClassificationTime = 17.201170835550826 * time = 65 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=DFR GB1} * accuracy = 0.7644144144144144 * precision = 0.8587619172032384 * recall = 0.8578530564466427 * f1-measure = 0.8583072462270525 * avgClassificationTime = 18.0178286322512 * time = 68 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=IB SPL-D} * accuracy = 0.5729437662597558 * precision = 0.7617216316318873 * recall = 0.7141873695627788 * f1-measure = 0.7371890380692823 * avgClassificationTime = 51.54523682810005 * time = 194 (sec) * KNearestNeighborClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=IB LL-L1} * accuracy = 0.7790802524797115 * precision = 0.8686406811181033 * recall = 0.8675778203762331 * f1-measure = 0.8681089254214804 * avgClassificationTime = 51.52847259180415 * time = 194 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=1, query=null, similarity=LM Jelinek-Mercer(0.300000)} * accuracy = 0.5679012345679012 * precision = 0.7749578318738607 * recall = 0.7091783225195025 * f1-measure = 0.7406103457621055 * avgClassificationTime = 144.6769722814499 * time = 543 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=1, query=null, similarity=IB LL-L1} * accuracy = 0.5770695530166366 * precision = 0.7783303390310153 * recall = 0.7175810572058965 * f1-measure = 0.7467221774528766 * avgClassificationTime = 146.2905117270789 * time = 549 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=1, query=null, similarity=ClassicSimilarity} * accuracy = 0.7471059661620659 * precision = 0.8502826626875049 * recall = 0.8471361378726211 * f1-measure = 0.8487064839053864 * avgClassificationTime = 167.71668443496802 * time = 629 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=ClassicSimilarity} * accuracy = 0.7620650953984287 * precision = 0.8603758289154071 * recall = 0.8566351023565671 * f1-measure = 0.8585013908118455 * avgClassificationTime = 167.81263326226014 * time = 630 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=1, query=null, similarity=BM25(k1=1.2,b=0.75)} * accuracy = 0.7554760840411265 * precision = 0.8535537275220065 * recall = 0.8529150601445842 * f1-measure = 0.8532342743186514 * avgClassificationTime = 136.93017057569296 * time = 514 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=BM25(k1=1.2,b=0.75)} * accuracy = 0.7631992810604359 * precision = 0.8586985644012539 * recall = 0.8566715130421416 * f1-measure = 0.8576838410392656 * avgClassificationTime = 145.19456289978677 * time = 545 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=F1EXP} * accuracy = 0.7479403250946337 * precision = 0.8498944455647027 * recall = 0.8465096638788843 * f1-measure = 0.848198677947652 * avgClassificationTime = 152.465618336887 * time = 572 (sec) * KNearestFuzzyClassifier{textFieldNames=[body], classFieldName='category', k=3, query=null, similarity=F1LOG} * accuracy = 0.7479403250946337 * precision = 0.8498944455647027 * recall = 0.8465096638788843 * f1-measure = 0.848198677947652 * avgClassificationTime = 152.04957356076758 * time = 571 (sec) * org.apache.lucene.classification.BM25NBClassifier@15d02688 * accuracy = 0.7478608100399315 * precision = 0.841994602444879 * recall = 0.8142580710691221 * f1-measure = 0.8278940910420016 * avgClassificationTime = 598.6328566677752 * time = 1800 (sec) * org.apache.lucene.classification.CachingNaiveBayesClassifier@3e1559f4 * accuracy = 0.5952332450600937 * precision = 0.7682827295013208 * recall = 0.7152730734523222 * f1-measure = 0.740830844538067 * avgClassificationTime = 16.914582224587548 * time = 64 (sec) * org.apache.lucene.classification.SimpleNaiveBayesClassifier@4fff0961 * accuracy = 0.5960400081649316 * precision = 0.7691620031408206 * recall = 0.7149946420941035 * f1-measure = 0.74108984777817 * avgClassificationTime = 161.94982652788897 * time = 607 (sec)
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