Results dump

Cross validation character n-grams tfidf

F1-score Task A 0.6440953412784399

              precision    recall  f1-score   support

           0  0.64831953 0.69214769 0.66951710      1923
           1  0.66760247 0.62218734 0.64409534      1911
           
   micro avg  0.65727700 0.65727700 0.65727700      3834
   macro avg  0.65796100 0.65716751 0.65680622      3834
weighted avg  0.65793082 0.65727700 0.65684601      3834

Embeddings with averages

F1-score Task A 0.5545722713864307
              precision    recall  f1-score   support

           0  0.70503597 0.62156448 0.66067416       473
           1  0.51226158 0.60450161 0.55457227       311

   micro avg  0.61479592 0.61479592 0.61479592       784
   macro avg  0.60864878 0.61303304 0.60762321       784
weighted avg  0.62856552 0.61479592 0.61858527       784

Embeddings with sums

F1-score Task A 0.3297644539614561
              precision    recall  f1-score   support

           0  0.62738854 0.83298097 0.71571299       473
           1  0.49358974 0.24758842 0.32976445       311

   micro avg  0.60076531 0.60076531 0.60076531       784
   macro avg  0.56048914 0.54028470 0.52273872       784
weighted avg  0.57431274 0.60076531 0.56261351       784

Trial data character n-grams tfidf


{'classify__C': 100, 'classify__gamma': 'scale', 'reduce_dim__k': 10000}
F1-score Task A 0.6191198786039454
              precision    recall  f1-score   support

           0  0.75458716 0.69556025 0.72387239       473
           1  0.58620690 0.65594855 0.61911988       311

   micro avg  0.67984694 0.67984694 0.67984694       784
   macro avg  0.67039703 0.67575440 0.67149613       784
weighted avg  0.68779346 0.67984694 0.68231878       784

Trial data character n-grams with cheating to match skew in test data

Best parameters: 
{'classify__C': 100, 'classify__class_weight': {0: 0.75, 1: 1.5}, 'classify__gamma': 'scale', 'reduce_dim__k': 10000}
F1-score Task A 0.6388206388206388
              precision    recall  f1-score   support

           0  0.81850534 0.48625793 0.61007958       473
           1  0.51689861 0.83601286 0.63882064       311

   micro avg  0.62500000 0.62500000 0.62500000       784
   macro avg  0.66770197 0.66113539 0.62445011       784
weighted avg  0.69886287 0.62500000 0.62148069       784

Trial data character n-grams mpqa skew in test data

MI

Fitting 5 folds for each of 5 candidates, totalling 25 fits
[Parallel(n_jobs=-1)]: Using backend LokyBackend with 16 concurrent workers.
[Parallel(n_jobs=-1)]: Done  20 out of  25 | elapsed:   14.3s remaining:    3.6s
[Parallel(n_jobs=-1)]: Done  25 out of  25 | elapsed:   14.4s finished
Grid scores on training set:

  'precision', 'predicted', average, warn_for)
              precision    recall  f1-score   support

           0  0.00000000 0.00000000 0.00000000       473
           1  0.39668367 1.00000000 0.56803653       311

   micro avg  0.39668367 0.39668367 0.39668367       784
   macro avg  0.19834184 0.50000000 0.28401826       784
weighted avg  0.15735794 0.39668367 0.22533082       784


Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.6067415730337078
              precision    recall  f1-score   support

           0  0.87931034 0.21564482 0.34634975       473
           1  0.44461078 0.95498392 0.60674157       311

   micro avg  0.50892857 0.50892857 0.50892857       784
   macro avg  0.66196056 0.58531437 0.47654566       784
weighted avg  0.70687212 0.50892857 0.44964293       784


Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.6211180124223602
              precision    recall  f1-score   support

           0  0.91472868 0.24947146 0.39202658       473
           1  0.45801527 0.96463023 0.62111801       311

   micro avg  0.53316327 0.53316327 0.53316327       784
   macro avg  0.68637197 0.60705084 0.50657230       784
weighted avg  0.73355793 0.53316327 0.48290341       784


Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.6282722513089005
              precision    recall  f1-score   support

           0  0.92142857 0.27272727 0.42088091       473
           1  0.46583851 0.96463023 0.62827225       311

   micro avg  0.54719388 0.54719388 0.54719388       784
   macro avg  0.69363354 0.61867875 0.52457658       784
weighted avg  0.74070343 0.54719388 0.50314967       784


Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.6251319957761351
              precision    recall  f1-score   support

           0  0.89864865 0.28118393 0.42834138       473
           1  0.46540881 0.95176849 0.62513200       311

   micro avg  0.54719388 0.54719388 0.54719388       784
   macro avg  0.68202873 0.61647621 0.52673669       784
weighted avg  0.72678948 0.54719388 0.50640501       784


Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.6272439281942978
              precision    recall  f1-score   support

           0  0.90540541 0.28329810 0.43156200       473
           1  0.46698113 0.95498392 0.62724393       311

   micro avg  0.54974490 0.54974490 0.54974490       784
   macro avg  0.68619327 0.61914101 0.52940296       784
weighted avg  0.73148965 0.54974490 0.50918582       784


Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.6314677930306231
              precision    recall  f1-score   support

           0  0.91891892 0.28752643 0.43800322       473
           1  0.47012579 0.96141479 0.63146779       311

   micro avg  0.55484694 0.55484694 0.55484694       784
   macro avg  0.69452235 0.62447061 0.53473551       784
weighted avg  0.74089001 0.55484694 0.51474746       784

Chi2

Grid scores on training set:

Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.5821596244131456
              precision    recall  f1-score   support

           0  0.96666667 0.06131078 0.11530815       473
           1  0.41114058 0.99678457 0.58215962       311

   micro avg  0.43239796 0.43239796 0.43239796       784
   macro avg  0.68890363 0.52904767 0.34873389       784
weighted avg  0.74629854 0.43239796 0.30050051       784

Best parameters: 
{'C': 10, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.5944881889763779
              precision    recall  f1-score   support

           0  0.88607595 0.14799154 0.25362319       473
           1  0.42836879 0.97106109 0.59448819       311

   micro avg  0.47448980 0.47448980 0.47448980       784
   macro avg  0.65722237 0.55952632 0.42405569       784
weighted avg  0.70451099 0.47448980 0.38883877       784

Best parameters: 
{'C': 10, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.59765625
              precision    recall  f1-score   support

           0  0.92957746 0.13953488 0.24264706       473
           1  0.42917251 0.98392283 0.59765625       311

   micro avg  0.47448980 0.47448980 0.47448980       784
   macro avg  0.67937499 0.56172886 0.42015165       784
weighted avg  0.73107499 0.47448980 0.38347341       784

Best parameters: 
{'C': 10, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.5996093750000001
              precision    recall  f1-score   support

           0  0.94366197 0.14164905 0.24632353       473
           1  0.43057504 0.98713826 0.59960938       311

   micro avg  0.47704082 0.47704082 0.47704082       784
   macro avg  0.68711850 0.56439366 0.42296645       784
weighted avg  0.74012876 0.47704082 0.38646626       784

Best parameters: 
{'C': 10, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.5974781765276431
              precision    recall  f1-score   support

           0  0.95312500 0.12896406 0.22718808       473
           1  0.42777778 0.99035370 0.59747818       311

   micro avg  0.47066327 0.47066327 0.47066327       784
   macro avg  0.69045139 0.55965888 0.41233313       784
weighted avg  0.74472833 0.47066327 0.37407612       784

Best parameters: 
{'C': 10, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.5926640926640927
              precision    recall  f1-score   support

           0  0.93220339 0.11627907 0.20676692       473
           1  0.42344828 0.98713826 0.59266409       311

   micro avg  0.46173469 0.46173469 0.46173469       784
   macro avg  0.67782583 0.55170867 0.39971550       784
weighted avg  0.73038854 0.46173469 0.35984603       784

Best parameters: 
{'C': 100, 'class_weight': {0: 0.7, 1: 1.5}, 'gamma': 'scale'}
F1-score Task A 0.6337854500616523
              precision    recall  f1-score   support

           0  0.80985915 0.48625793 0.60766182       473
           1  0.51400000 0.82636656 0.63378545       311

   micro avg  0.62117347 0.62117347 0.62117347       784
   macro avg  0.66192958 0.65631224 0.62072364       784
weighted avg  0.69249666 0.62117347 0.61802464       784

Sentiment feats alone

              precision    recall  f1-score   support

           0  0.63468635 0.36363636 0.46236559       473
           1  0.41325536 0.68167203 0.51456311       311

   micro avg  0.48979592 0.48979592 0.48979592       784
   macro avg  0.52397085 0.52265419 0.48846435       784
weighted avg  0.54684829 0.48979592 0.48307149       784

MPQA Sentiment feats + BoW

MI

Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.5987421383647799
              precision    recall  f1-score   support

           0  0.75666667 0.47991543 0.58732212       473
           1  0.49173554 0.76527331 0.59874214       311

   micro avg  0.59311224 0.59311224 0.59311224       784
   macro avg  0.62420110 0.62259437 0.59303213       784
weighted avg  0.65157281 0.59311224 0.59185226       784

Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6122905027932961
              precision    recall  f1-score   support

           0  0.81500000 0.34460888 0.48439822       473
           1  0.46917808 0.88102894 0.61229050       311

   micro avg  0.55739796 0.55739796 0.55739796       784
   macro avg  0.64208904 0.61281891 0.54834436       784
weighted avg  0.67781809 0.55739796 0.53513100       784

Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6160714285714285
              precision    recall  f1-score   support

           0  0.82412060 0.34672304 0.48809524       473
           1  0.47179487 0.88745981 0.61607143       311

   micro avg  0.56122449 0.56122449 0.56122449       784
   macro avg  0.64795774 0.61709143 0.55208333       784
weighted avg  0.68435874 0.56122449 0.53886130       784

Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6155555555555555
              precision    recall  f1-score   support

           0  0.82564103 0.34038055 0.48203593       473
           1  0.47028862 0.89067524 0.61555556       311

   micro avg  0.55867347 0.55867347 0.55867347       784
   macro avg  0.64796483 0.61552790 0.54879574       784
weighted avg  0.68467853 0.55867347 0.53500098       784

Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6145374449339207
              precision    recall  f1-score   support

           0  0.82887701 0.32769556 0.46969697       473
           1  0.46733668 0.89710611 0.61453744       311

   micro avg  0.55357143 0.55357143 0.55357143       784
   macro avg  0.64810684 0.61240083 0.54211721       784
weighted avg  0.68545986 0.55357143 0.52715282       784

Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6106870229007634
              precision    recall  f1-score   support

           0  0.82584270 0.31078224 0.45161290       473
           1  0.46204620 0.90032154 0.61068702       311

   micro avg  0.54464286 0.54464286 0.54464286       784
   macro avg  0.64394445 0.60555189 0.53114996       784
weighted avg  0.68153057 0.54464286 0.51471501       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6352941176470589
              precision    recall  f1-score   support

           0  0.79393939 0.55391121 0.65255293       473
           1  0.53524229 0.78135048 0.63529412       311

   micro avg  0.64413265 0.64413265 0.64413265       784
   macro avg  0.66459084 0.66763084 0.64392352       784
weighted avg  0.69131848 0.64413265 0.64570664       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.639386189258312
              precision    recall  f1-score   support

           0  0.80511182 0.53276956 0.64122137       473
           1  0.53078556 0.80385852 0.63938619       311

   micro avg  0.64030612 0.64030612 0.64030612       784
   macro avg  0.66794869 0.66831404 0.64030378       784
weighted avg  0.69629107 0.64030612 0.64049339       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.645
              precision    recall  f1-score   support

           0  0.82033898 0.51162791 0.63020833       473
           1  0.52760736 0.82958199 0.64500000       311

   micro avg  0.63775510 0.63775510 0.63775510       784
   macro avg  0.67397317 0.67060495 0.63760417       784
weighted avg  0.70421713 0.63775510 0.63607595       784

Chi2

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6114352392065344
              precision    recall  f1-score   support

           0  0.79411765 0.39957717 0.53164557       473
           1  0.47985348 0.84244373 0.61143524       311

   micro avg  0.57525510 0.57525510 0.57525510       784
   macro avg  0.63698556 0.62101045 0.57154040       784
weighted avg  0.66945418 0.57525510 0.56329683       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6084425036390102
              precision    recall  f1-score   support

           0  0.75000000 0.64693446 0.69466515       473
           1  0.55585106 0.67202572 0.60844250       311

   micro avg  0.65688776 0.65688776 0.65688776       784
   macro avg  0.65292553 0.65948009 0.65155383       784
weighted avg  0.67298429 0.65688776 0.66046204       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5892857142857142
              precision    recall  f1-score   support

           0  0.73286052 0.65539112 0.69196429       473
           1  0.54847645 0.63665595 0.58928571       311

   micro avg  0.64795918 0.64795918 0.64795918       784
   macro avg  0.64066849 0.64602353 0.64062500       784
weighted avg  0.65971837 0.64795918 0.65123337       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5991058122205664
              precision    recall  f1-score   support

           0  0.74056604 0.66384778 0.70011148       473
           1  0.55833333 0.64630225 0.59910581       311

   micro avg  0.65688776 0.65688776 0.65688776       784
   macro avg  0.64944969 0.65507502 0.64960865       784
weighted avg  0.66827730 0.65688776 0.66004418       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6240928882438316
              precision    recall  f1-score   support

           0  0.76354680 0.65539112 0.70534699       473
           1  0.56878307 0.69131833 0.62409289       311

   micro avg  0.66964286 0.66964286 0.66964286       784
   macro avg  0.66616493 0.67335472 0.66471994       784
weighted avg  0.68628721 0.66964286 0.67311481       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6195965417867435
              precision    recall  f1-score   support

           0  0.76059850 0.64482030 0.69794050       473
           1  0.56135770 0.69131833 0.61959654       311

   micro avg  0.66326531 0.66326531 0.66326531       784
   macro avg  0.66097810 0.66806931 0.65876852       784
weighted avg  0.68156293 0.66326531 0.66686273       784


Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6218978102189782
              precision    recall  f1-score   support

           0  0.76097561 0.65961945 0.70668177       473
           1  0.56951872 0.68488746 0.62189781       311

   micro avg  0.66964286 0.66964286 0.66964286       784
   macro avg  0.66524716 0.67225346 0.66428979       784
weighted avg  0.68502779 0.66964286 0.67304936       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6440677966101694
              precision    recall  f1-score   support

           0  0.80487805 0.55813953 0.65917603       473
           1  0.54166667 0.79421222 0.64406780       311

   micro avg  0.65178571 0.65178571 0.65178571       784
   macro avg  0.67327236 0.67617588 0.65162191       784
weighted avg  0.70046639 0.65178571 0.65318284       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.644918444165621
              precision    recall  f1-score   support

           0  0.81879195 0.51585624 0.63294423       473
           1  0.52880658 0.82636656 0.64491844       311

   micro avg  0.63903061 0.63903061 0.63903061       784
   macro avg  0.67379927 0.67111140 0.63893134       784
weighted avg  0.70375949 0.63903061 0.63769420       784

CoreNLP Sentiment feats + BOW

MI

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5388127853881278
              precision    recall  f1-score   support

           0  0.69406393 0.64270613 0.66739846       473
           1  0.51156069 0.56913183 0.53881279       311

   micro avg  0.61352041 0.61352041 0.61352041       784
   macro avg  0.60281231 0.60591898 0.60310562       784
weighted avg  0.62166787 0.61352041 0.61639062       784


Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5680119581464873
              precision    recall  f1-score   support

           0  0.71596244 0.64482030 0.67853170       473
           1  0.53072626 0.61093248 0.56801196       311

   micro avg  0.63137755 0.63137755 0.63137755       784
   macro avg  0.62334435 0.62787639 0.62327183       784
weighted avg  0.64248227 0.63137755 0.63469032       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5727272727272729
              precision    recall  f1-score   support

           0  0.71954023 0.66173362 0.68942731       473
           1  0.54154728 0.60771704 0.57272727       311

   micro avg  0.64030612 0.64030612 0.64030612       784
   macro avg  0.63054375 0.63472533 0.63107729       784
weighted avg  0.64893333 0.64030612 0.64313431       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6156111929307806
              precision    recall  f1-score   support

           0  0.75480769 0.66384778 0.70641170       473
           1  0.56793478 0.67202572 0.61561119       311

   micro avg  0.66709184 0.66709184 0.66709184       784
   macro avg  0.66137124 0.66793675 0.66101145       784
weighted avg  0.68067826 0.66709184 0.67039262       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6056971514242879
              precision    recall  f1-score   support

           0  0.74532710 0.67441860 0.70810211       473
           1  0.56741573 0.64951768 0.60569715       311

   micro avg  0.66454082 0.66454082 0.66454082       784
   macro avg  0.65637142 0.66196814 0.65689963       784
weighted avg  0.67475257 0.66454082 0.66747973       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6217008797653958
              precision    recall  f1-score   support

           0  0.76029056 0.66384778 0.70880361       473
           1  0.57142857 0.68167203 0.62170088       311

   micro avg  0.67091837 0.67091837 0.67091837       784
   macro avg  0.66585956 0.67275990 0.66525225       784
weighted avg  0.68537209 0.67091837 0.67425138       784


Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6133333333333333
              precision    recall  f1-score   support

           0  0.75238095 0.66807611 0.70772676       473
           1  0.56868132 0.66559486 0.61333333       311

   micro avg  0.66709184 0.66709184 0.66709184       784
   macro avg  0.66053114 0.66683548 0.66053005       784
weighted avg  0.67951031 0.66709184 0.67028243       784

F1-score Task A 0.6105263157894737
              precision    recall  f1-score   support

           0  0.74883721 0.68076110 0.71317829       473
           1  0.57344633 0.65273312 0.61052632       311

   micro avg  0.66964286 0.66964286 0.66964286       784
   macro avg  0.66114177 0.66674711 0.66185231       784
weighted avg  0.67926251 0.66964286 0.67245793       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6240713224368498
              precision    recall  f1-score   support

           0  0.76066351 0.67864693 0.71731844       473
           1  0.58011050 0.67524116 0.62407132       311

   micro avg  0.67729592 0.67729592 0.67729592       784
   macro avg  0.67038700 0.67694405 0.67069488       784
weighted avg  0.68904108 0.67729592 0.68032883       784

Chi2

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5799457994579946
              precision    recall  f1-score   support

           0  0.72829132 0.54968288 0.62650602       473
           1  0.50117096 0.68810289 0.57994580       311

   micro avg  0.60459184 0.60459184 0.60459184       784
   macro avg  0.61473114 0.61889288 0.60322591       784
weighted avg  0.63819638 0.60459184 0.60803634       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5900151285930408
              precision    recall  f1-score   support

           0  0.73271889 0.67230444 0.70121279       473
           1  0.55714286 0.62700965 0.59001513       311

   micro avg  0.65433673 0.65433673 0.65433673       784
   macro avg  0.64493088 0.64965704 0.64561396       784
weighted avg  0.66307075 0.65433673 0.65710249       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6184012066365008
              precision    recall  f1-score   support

           0  0.75462963 0.68921776 0.72044199       473
           1  0.58238636 0.65916399 0.61840121       311

   micro avg  0.67729592 0.67729592 0.67729592       784
   macro avg  0.66850800 0.67419087 0.66942160       784
weighted avg  0.68630354 0.67729592 0.67996408       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5988023952095808
              precision    recall  f1-score   support

           0  0.74004684 0.66807611 0.70222222       473
           1  0.56022409 0.64308682 0.59880240       311

   micro avg  0.65816327 0.65816327 0.65816327       784
   macro avg  0.65013546 0.65558146 0.65051231       784
weighted avg  0.66871409 0.65816327 0.66119727       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6133333333333333
              precision    recall  f1-score   support

           0  0.75238095 0.66807611 0.70772676       473
           1  0.56868132 0.66559486 0.61333333       311

   micro avg  0.66709184 0.66709184 0.66709184       784
   macro avg  0.66053114 0.66683548 0.66053005       784
weighted avg  0.67951031 0.66709184 0.67028243       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6332842415316642
              precision    recall  f1-score   support

           0  0.76923077 0.67653277 0.71991001       473
           1  0.58423913 0.69131833 0.63328424       311

   micro avg  0.68239796 0.68239796 0.68239796       784
   macro avg  0.67673495 0.68392555 0.67659713       784
weighted avg  0.69584761 0.68239796 0.68554698       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6117647058823529
              precision    recall  f1-score   support

           0  0.75180723 0.65961945 0.70270270       473
           1  0.56368564 0.66881029 0.61176471       311

   micro avg  0.66326531 0.66326531 0.66326531       784
   macro avg  0.65774643 0.66421487 0.65723370       784
weighted avg  0.67718246 0.66326531 0.66662908       784

F1-score Task A 0.6172106824925816
              precision    recall  f1-score   support

           0  0.75534442 0.67230444 0.71140940       473
           1  0.57300275 0.66881029 0.61721068       311

   micro avg  0.67091837 0.67091837 0.67091837       784
   macro avg  0.66417359 0.67055736 0.66431004       784
weighted avg  0.68301246 0.67091837 0.67404230       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6140089418777943
              precision    recall  f1-score   support

           0  0.75235849 0.67441860 0.71125975       473
           1  0.57222222 0.66237942 0.61400894       311

   micro avg  0.66964286 0.66964286 0.66964286       784
   macro avg  0.66229036 0.66839901 0.66263435       784
weighted avg  0.68090137 0.66964286 0.67268195       784

Twitter Sentiment feats + BOW

Mutual Information

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.5710186513629842
              precision    recall  f1-score   support

           0  0.71859296 0.60465116 0.65671642       473
           1  0.51554404 0.63987138 0.57101865       311

   micro avg  0.61862245 0.61862245 0.61862245       784
   macro avg  0.61706850 0.62226127 0.61386753       784
weighted avg  0.63804677 0.61862245 0.62272151       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.5918653576437587
              precision    recall  f1-score   support

           0  0.73821990 0.59619450 0.65964912       473
           1  0.52487562 0.67845659 0.59186536       311

   micro avg  0.62882653 0.62882653 0.62882653       784
   macro avg  0.63154776 0.63732555 0.62575724       784
weighted avg  0.65358971 0.62882653 0.63276041       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.5963431786216595
              precision    recall  f1-score   support

           0  0.74218750 0.60253700 0.66511085       473
           1  0.53000000 0.68167203 0.59634318       311

   micro avg  0.63392857 0.63392857 0.63392857       784
   macro avg  0.63609375 0.64210451 0.63072702       784
weighted avg  0.65801618 0.63392857 0.63783184       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6134800550206327
              precision    recall  f1-score   support

           0  0.76086957 0.59196617 0.66587396       473
           1  0.53605769 0.71704180 0.61348006       311

   micro avg  0.64158163 0.64158163 0.64158163       784
   macro avg  0.64846363 0.65450399 0.63967701       784
weighted avg  0.67169037 0.64158163 0.64509015       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6253443526170799
              precision    recall  f1-score   support

           0  0.77235772 0.60253700 0.67695962       473
           1  0.54698795 0.72990354 0.62534435       311

   micro avg  0.65306122 0.65306122 0.65306122       784
   macro avg  0.65967284 0.66622027 0.65115199       784
weighted avg  0.68295721 0.65306122 0.65648469       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6233062330623307
              precision    recall  f1-score   support

           0  0.77310924 0.58350951 0.66506024       473
           1  0.53864169 0.73954984 0.62330623       311

   micro avg  0.64540816 0.64540816 0.64540816       784
   macro avg  0.65587546 0.66152968 0.64418324       784
weighted avg  0.68009979 0.64540816 0.64849711       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6228187919463087
              precision    recall  f1-score   support

           0  0.77428571 0.57293869 0.65856622       473
           1  0.53456221 0.74598071 0.62281879       311

   micro avg  0.64158163 0.64158163 0.64158163       784
   macro avg  0.65442396 0.65945970 0.64069251       784
weighted avg  0.67919131 0.64158163 0.64438580       784

Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6251655629139073
              precision    recall  f1-score   support

           0  0.77941176 0.56025370 0.65190652       473
           1  0.53153153 0.75884244 0.62516556       311

   micro avg  0.63903061 0.63903061 0.63903061       784
   macro avg  0.65547165 0.65954807 0.63853604       784
weighted avg  0.68108172 0.63903061 0.64129882       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6276041666666666
              precision    recall  f1-score   support

           0  0.78593272 0.54334038 0.64250000       473
           1  0.52735230 0.77491961 0.62760417       311

   micro avg  0.63520408 0.63520408 0.63520408       784
   macro avg  0.65664251 0.65913000 0.63505208       784
weighted avg  0.68335809 0.63520408 0.63659107       784

Chi-squared


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6
              precision    recall  f1-score   support

           0  0.76140351 0.45877378 0.57255937       473
           1  0.48697395 0.78135048 0.60000000       311

   micro avg  0.58673469 0.58673469 0.58673469       784
   macro avg  0.62418873 0.62006213 0.58627968       784
weighted avg  0.65254178 0.58673469 0.58344462       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5842349304482226
              precision    recall  f1-score   support

           0  0.72767857 0.68921776 0.70792617       473
           1  0.56250000 0.60771704 0.58423493       311

   micro avg  0.65688776 0.65688776 0.65688776       784
   macro avg  0.64508929 0.64846740 0.64608055       784
weighted avg  0.66215493 0.65688776 0.65885987       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6183431952662721
              precision    recall  f1-score   support

           0  0.75656325 0.67019027 0.71076233       473
           1  0.57260274 0.67202572 0.61834320       311

   micro avg  0.67091837 0.67091837 0.67091837       784
   macro avg  0.66458299 0.67110800 0.66455276       784
weighted avg  0.68358912 0.67091837 0.67410117       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.623688155922039
              precision    recall  f1-score   support

           0  0.75934579 0.68710359 0.72142064       473
           1  0.58426966 0.66881029 0.62368816       311

   micro avg  0.67984694 0.67984694 0.67984694       784
   macro avg  0.67180773 0.67795694 0.67255440       784
weighted avg  0.68989595 0.67984694 0.68265176       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.624813153961136
              precision    recall  f1-score   support

           0  0.76056338 0.68498943 0.72080089       473
           1  0.58379888 0.67202572 0.62481315       311

   micro avg  0.67984694 0.67984694 0.67984694       784
   macro avg  0.67218113 0.67850758 0.67280702       784
weighted avg  0.69044379 0.67984694 0.68272412       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6340740740740741
              precision    recall  f1-score   support

           0  0.76904762 0.68287526 0.72340426       473
           1  0.58791209 0.68810289 0.63407407       311

   micro avg  0.68494898 0.68494898 0.68494898       784
   macro avg  0.67847985 0.68548908 0.67873916       784
weighted avg  0.69719411 0.68494898 0.68796843       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.609720176730486
              precision    recall  f1-score   support

           0  0.75000000 0.65961945 0.70191226       473
           1  0.56250000 0.66559486 0.60972018       311

   micro avg  0.66198980 0.66198980 0.66198980       784
   macro avg  0.65625000 0.66260715 0.65581622       784
weighted avg  0.67562181 0.66198980 0.66534117       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6244477172312224
              precision    recall  f1-score   support

           0  0.76201923 0.67019027 0.71316085       473
           1  0.57608696 0.68167203 0.62444772       311

   micro avg  0.67474490 0.67474490 0.67474490       784
   macro avg  0.66905309 0.67593115 0.66880429       784
weighted avg  0.68826293 0.67474490 0.67796980       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6311688311688313
              precision    recall  f1-score   support

           0  0.79076923 0.54334038 0.64411028       473
           1  0.52941176 0.78135048 0.63116883       311

   micro avg  0.63775510 0.63775510 0.63775510       784
   macro avg  0.66009050 0.66234543 0.63763955       784
weighted avg  0.68709299 0.63775510 0.63897662       784

Bow alone

Mutual Information

Best parameters: 
{'C': 0.01, 'gamma': 'scale'}
F1-score Task A 0.6146788990825688
              precision    recall  f1-score   support

           0  0.80717489 0.38054968 0.51724138       473
           1  0.47771836 0.86173633 0.61467890       311

   micro avg  0.57142857 0.57142857 0.57142857       784
   macro avg  0.64244662 0.62114301 0.56596014       784
weighted avg  0.67648486 0.57142857 0.55589325       784


Best parameters: 
{'C': 0.1, 'gamma': 'scale'}
F1-score Task A 0.6074766355140188
              precision    recall  f1-score   support

           0  0.78661088 0.39746300 0.52808989       473
           1  0.47706422 0.83601286 0.60747664       311

   micro avg  0.57142857 0.57142857 0.57142857       784
   macro avg  0.63183755 0.61673793 0.56778326       784
weighted avg  0.66381877 0.57142857 0.55958131       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6084507042253521
              precision    recall  f1-score   support

           0  0.75324675 0.61310782 0.67599068       473
           1  0.54135338 0.69453376 0.60845070       311

   micro avg  0.64540816 0.64540816 0.64540816       784
   macro avg  0.64730007 0.65382079 0.64222069       784
weighted avg  0.66919211 0.64540816 0.64919867       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6022727272727273
              precision    recall  f1-score   support

           0  0.74680307 0.61733615 0.67592593       473
           1  0.53944020 0.68167203 0.60227273       311

   micro avg  0.64285714 0.64285714 0.64285714       784
   macro avg  0.64312164 0.64950409 0.63909933       784
weighted avg  0.66454561 0.64285714 0.64670890       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.5991316931982634
              precision    recall  f1-score   support

           0  0.74257426 0.63424947 0.68415051       473
           1  0.54473684 0.66559486 0.59913169       311

   micro avg  0.64668367 0.64668367 0.64668367       784
   macro avg  0.64365555 0.64992216 0.64164110       784
weighted avg  0.66409538 0.64668367 0.65042494       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6080691642651297
              precision    recall  f1-score   support

           0  0.75062344 0.63636364 0.68878719       473
           1  0.55091384 0.67845659 0.60806916       311

   micro avg  0.65306122 0.65306122 0.65306122       784
   macro avg  0.65076864 0.65741011 0.64842817       784
weighted avg  0.67140190 0.65306122 0.65676766       784


Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6242038216560509
              precision    recall  f1-score   support

           0  0.78709677 0.51585624 0.62324393       473
           1  0.51687764 0.78778135 0.62420382       311

   micro avg  0.62372449 0.62372449 0.62372449       784
   macro avg  0.65198721 0.65181879 0.62372388       784
weighted avg  0.67990525 0.62372449 0.62362471       784


Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6221662468513853
              precision    recall  f1-score   support

           0  0.78737542 0.50105708 0.61240310       473
           1  0.51138716 0.79421222 0.62216625       311

   micro avg  0.61734694 0.61734694 0.61734694       784
   macro avg  0.64938129 0.64763465 0.61728467       784
weighted avg  0.67789538 0.61734694 0.61627598       784

Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6262376237623762
              precision    recall  f1-score   support

           0  0.79790941 0.48414376 0.60263158       473
           1  0.50905433 0.81350482 0.62623762       311

   micro avg  0.61479592 0.61479592 0.61479592       784
   macro avg  0.65348187 0.64882429 0.61443460       784
weighted avg  0.68332531 0.61479592 0.61199571       784

Chi2

Best parameters: 
{'C': 0.1, 'gamma': 'scale'}
F1-score Task A 0.616822429906542
              precision    recall  f1-score   support

           0  0.80334728 0.40591966 0.53932584       473
           1  0.48440367 0.84887460 0.61682243       311

   micro avg  0.58163265 0.58163265 0.58163265       784
   macro avg  0.64387548 0.62739713 0.57807414       784
weighted avg  0.67682756 0.58163265 0.57006747       784


Best parameters: 
{'C': 0.1, 'gamma': 'scale'}
F1-score Task A 0.6134259259259259
              precision    recall  f1-score   support

           0  0.80086580 0.39112051 0.52556818       473
           1  0.47920434 0.85209003 0.61342593       311

   micro avg  0.57397959 0.57397959 0.57397959       784
   macro avg  0.64003507 0.62160527 0.56949705       784
weighted avg  0.67326795 0.57397959 0.56041991       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6005830903790088
              precision    recall  f1-score   support

           0  0.74327628 0.64270613 0.68934240       473
           1  0.54933333 0.66237942 0.60058309       311

   micro avg  0.65051020 0.65051020 0.65051020       784
   macro avg  0.64630481 0.65254278 0.64496275       784
weighted avg  0.66634228 0.65051020 0.65413303       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6051873198847262
              precision    recall  f1-score   support

           0  0.74812968 0.63424947 0.68649886       473
           1  0.54830287 0.67524116 0.60518732       311

   micro avg  0.65051020 0.65051020 0.65051020       784
   macro avg  0.64821627 0.65474531 0.64584309       784
weighted avg  0.66886165 0.65051020 0.65424390       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.5979971387696709
              precision    recall  f1-score   support

           0  0.74242424 0.62156448 0.67663982       473
           1  0.53865979 0.67202572 0.59799714       311

   micro avg  0.64158163 0.64158163 0.64158163       784
   macro avg  0.64054202 0.64679510 0.63731848       784
weighted avg  0.66159421 0.64158163 0.64544355       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6189111747851003
              precision    recall  f1-score   support

           0  0.76070529 0.63847780 0.69425287       473
           1  0.55813953 0.69453376 0.61891117       311

   micro avg  0.66071429 0.66071429 0.66071429       784
   macro avg  0.65942241 0.66650578 0.65658202       784
weighted avg  0.68035076 0.66071429 0.66436605       784


Best parameters: 
{'C': 10, 'gamma': 'scale'}
F1-score Task A 0.6221590909090909
              precision    recall  f1-score   support

           0  0.76470588 0.63213531 0.69212963       473
           1  0.55725191 0.70418006 0.62215909       311

   micro avg  0.66071429 0.66071429 0.66071429       784
   macro avg  0.66097890 0.66815769 0.65714436       784
weighted avg  0.68241228 0.66071429 0.66437346       784


Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.628498727735369
              precision    recall  f1-score   support

           0  0.79288026 0.51797040 0.62659847       473
           1  0.52000000 0.79421222 0.62849873       311

   micro avg  0.62755102 0.62755102 0.62755102       784
   macro avg  0.65644013 0.65609131 0.62754860       784
weighted avg  0.68463312 0.62755102 0.62735227       784


Best parameters: 
{'C': 1, 'gamma': 'scale'}
F1-score Task A 0.6236024844720497
              precision    recall  f1-score   support

           0  0.79310345 0.48625793 0.60288336       473
           1  0.50809717 0.80707395 0.62360248       311

   micro avg  0.61352041 0.61352041 0.61352041       784
   macro avg  0.65060031 0.64666594 0.61324292       784
weighted avg  0.68004611 0.61352041 0.61110230       784

Combined

Chi2

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5663716814159292
              precision    recall  f1-score   support

           0  0.71462830 0.63002114 0.66966292       473
           1  0.52316076 0.61736334 0.56637168       311

   micro avg  0.62500000 0.62500000 0.62500000       784
   macro avg  0.61889453 0.62369224 0.61801730       784
weighted avg  0.63867625 0.62500000 0.62868897       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5753012048192772
              precision    recall  f1-score   support

           0  0.72157773 0.65750529 0.68805310       473
           1  0.54107649 0.61414791 0.57530120       311

   micro avg  0.64030612 0.64030612 0.64030612       784
   macro avg  0.63132711 0.63582660 0.63167715       784
weighted avg  0.64997583 0.64030612 0.64332626       784


Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5954198473282442
              precision    recall  f1-score   support

           0  0.73636364 0.68498943 0.70974808       473
           1  0.56686047 0.62700965 0.59541985       311

   micro avg  0.66198980 0.66198980 0.66198980       784
   macro avg  0.65161205 0.65599954 0.65258397       784
weighted avg  0.66912450 0.66198980 0.66439594       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.600609756097561
              precision    recall  f1-score   support

           0  0.74031891 0.68710359 0.71271930       473
           1  0.57101449 0.63344051 0.60060976       311

   micro avg  0.66581633 0.66581633 0.66581633       784
   macro avg  0.65566670 0.66027205 0.65666453       784
weighted avg  0.67315861 0.66581633 0.66824727       784


Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6255639097744361
              precision    recall  f1-score   support

           0  0.76046512 0.69133192 0.72425249       473
           1  0.58757062 0.66881029 0.62556391       311

   micro avg  0.68239796 0.68239796 0.68239796       784
   macro avg  0.67401787 0.68007111 0.67490820       784
weighted avg  0.69188069 0.68239796 0.68510434       784


Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6216216216216217
              precision    recall  f1-score   support

           0  0.75757576 0.68710359 0.72062084       473
           1  0.58309859 0.66559486 0.62162162       311

   micro avg  0.67857143 0.67857143 0.67857143       784
   macro avg  0.67033717 0.67634922 0.67112123       784
weighted avg  0.68836351 0.67857143 0.68134947       784


Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6077844311377245
              precision    recall  f1-score   support

           0  0.74707260 0.67441860 0.70888889       473
           1  0.56862745 0.65273312 0.60778443       311

   micro avg  0.66581633 0.66581633 0.66581633       784
   macro avg  0.65785003 0.66357586 0.65833666       784
weighted avg  0.67628632 0.66581633 0.66878240       784

Mutual Information

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5601217656012177
              precision    recall  f1-score   support

           0  0.71004566 0.65750529 0.68276619       473
           1  0.53179191 0.59163987 0.56012177       311

   micro avg  0.63137755 0.63137755 0.63137755       784
   macro avg  0.62091878 0.62457258 0.62144398       784
weighted avg  0.63933531 0.63137755 0.63411515       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.5753424657534247
              precision    recall  f1-score   support

           0  0.72146119 0.66807611 0.69374314       473
           1  0.54624277 0.60771704 0.57534247       311

   micro avg  0.64413265 0.64413265 0.64413265       784
   macro avg  0.63385198 0.63789658 0.63454280       784
weighted avg  0.65195490 0.64413265 0.64677553       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.581039755351682
              precision    recall  f1-score   support

           0  0.72562358 0.67653277 0.70021882       473
           1  0.55393586 0.61093248 0.58103976       311

   micro avg  0.65051020 0.65051020 0.65051020       784
   macro avg  0.63977972 0.64373262 0.64062929       784
weighted avg  0.65751787 0.65051020 0.65294243       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6066066066066067
              precision    recall  f1-score   support

           0  0.74592075 0.67653277 0.70953437       473
           1  0.56901408 0.64951768 0.60660661       311

   micro avg  0.66581633 0.66581633 0.66581633       784
   macro avg  0.65746742 0.66302523 0.65807049       784
weighted avg  0.67574476 0.66581633 0.66870461       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6059701492537314
              precision    recall  f1-score   support

           0  0.74588235 0.67019027 0.70601336       473
           1  0.56545961 0.65273312 0.60597015       311

   micro avg  0.66326531 0.66326531 0.66326531       784
   macro avg  0.65567098 0.66146170 0.65599176       784
weighted avg  0.67431160 0.66326531 0.66632785       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.608955223880597
              precision    recall  f1-score   support

           0  0.74823529 0.67230444 0.70824053       473
           1  0.56824513 0.65594855 0.60895522       311

   micro avg  0.66581633 0.66581633 0.66581633       784
   macro avg  0.65824021 0.66412650 0.65859788       784
weighted avg  0.67683613 0.66581633 0.66885567       784

Best parameters: 
{'C': 100, 'gamma': 'scale'}
F1-score Task A 0.6063348416289592
              precision    recall  f1-score   support

           0  0.74537037 0.68076110 0.71160221       473
           1  0.57102273 0.64630225 0.60633484       311

   micro avg  0.66709184 0.66709184 0.66709184       784
   macro avg  0.65819655 0.66353168 0.65896853       784
weighted avg  0.67620951 0.66709184 0.66984436       784


Revision #33
Created Tue, Jan 22, 2019 4:15 AM by kenneth
Updated Thu, Feb 6, 2020 4:53 PM by kenneth