daskframe/__init__.py,sha256=lJODunzHVeGtIYyHG4OJumH5M7IB32ybMj5bmDi-VpA,105
daskframe/_version.py,sha256=QR3GgexnAm-h1hlSkp42NFRXV67a7qGktmBetenX-d8,23
daskframe/base_functions.py,sha256=07afVJ2eLfCgYtFD2_6L8yC_kIm7FCo5HOLo9qTL_cc,1214
daskframe/columns.py,sha256=776DtBrhj5bcPSJRDDbUTDl9AGArUOhnZ8okIz7M7iU,6803
daskframe/converter.py,sha256=Ys1_qun0EKXYsHqU9nhg353iJwjzniZjVxsO0MjggLc,1582
daskframe/create.py,sha256=I3LWxediVAqKk0rss1TJZyk2CWFCKYKE1-scPAfiSIM,341
daskframe/dask_functions.py,sha256=moUXo2XpHaqKYKzTSagu7iZ2b1ujzyiJaYl3TRK3x0Y,4076
daskframe/dataframe.py,sha256=rfkONYrGSe2d2pR5g8H4dhrQkZxVe6JfQjNQBlruGxw,6848
daskframe/expressions.py,sha256=5vgIGwIgQcng-ApSHvkQVTmdItVhVSeWSEidZo9atqc,21150
daskframe/jit.py,sha256=9qwhL_V9XJGgUJkDS_LuBotDEupoYWvlDzFWIFPuqIM,3927
daskframe/rows.py,sha256=a8Q44zmKjv8Bhx4QkSx5mO_t99WitYd0l67txLT3fuc,29768
daskframe/utils.py,sha256=xY-8WpwG06XlSycErgawSJn1_f5iZJCgedE8M9Qsfuk,9732
daskframe/io/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
daskframe/io/create.py,sha256=cp9LM3gLW04OcgKu1wULdFH-ftceNcB52MrzjVfbjCc,3290
daskframe/io/load.py,sha256=ThBACzq0-xqx9qCwRtOkC7xc7dpz71vt_mMuioc-5rg,10993
daskframe/io/save.py,sha256=n7T_YZ5rL6Z0VRmW_0wAuHZV8vhW78E-m4hm0lu-W34,2011
kolibri/__init__.py,sha256=tUQ38dJejJnY3UZvNNJqtkEZVarnlqBV702otssBZtE,289
kolibri/config.py,sha256=nFYNd79w8Bb3P1dofYo8m8Bb1hG5UE4wpH-3bY2DKqg,3553
kolibri/errors.py,sha256=uDJvsWJ9zJTsJ81zjLU4lPhqq8scN4-d4yerXJC1n0Y,3181
kolibri/logger.py,sha256=oGWvE_x74dPGTJgTNbVev8kiVrU7ZC5BRwYPsDfiyEw,685
kolibri/metadata.py,sha256=OVFWni8xWbijx4eTXh12pyx-riztAiw-Y4Zlv1Ay6Ks,2226
kolibri/model_loader.py,sha256=tpYdo9OOeSsODn85BEhWjb-EkmLVvpX7D1-htx-p0QY,5126
kolibri/model_trainer.py,sha256=-pxKM2Hn8SyD83JZrgcCq5FNikrlsraVaknjGK5BfEc,8276
kolibri/registry.py,sha256=gTbTqCqLI9LtFQYPzKL0kLwelVO3uG6yiibvYzYR2RY,1494
kolibri/settings.py,sha256=D-Fv26XuWhQxwfDYO3YVmsxY4iF_juvDTiItRATZ_cA,2498
kolibri/version.py,sha256=3Clx6PzqZtLlqciDZfjzZTEc2KrmzE5ZGnFT2yQSkGE,23
kolibri/autolearn/__init__.py,sha256=1Sa6JmRk2g2Do8G3A2oSktslASAu9JXg27OQZYXJkOk,66
kolibri/autolearn/metalearn/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/autolearn/metalearn/metafeature.py,sha256=ZYDEZbG8uBKOI-ORMZJ7U5dUdCuIZ9l8XvayBCTpRM8,3115
kolibri/autolearn/metalearn/metafeatures.py,sha256=d43ZAEYIvrdRLPu4tPNYh1A6PD9YAAUySLUommeyiwU,46866
kolibri/autolearn/model_zoo/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/autolearn/model_zoo/zoo_estimator.py,sha256=RI9CZ_GwtkqyXkc7HeZCPCTpdiSG6lNbgP6WVatCeCo,5940
kolibri/backend/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/backend/models.py,sha256=tLhlfOBkTBTDktxCkk8OJnHA-bxNLNBbo1jddcAM7A0,6408
kolibri/backend/base/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/backend/base/estimator.py,sha256=L6y0rfUpZS3apjjzof6AFr70WMrP0sQ-XnzTapQ7vFc,14923
kolibri/backend/sklearn/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/backend/sklearn/meta/__init__.py,sha256=YvrffJMeN_MHWddQAwtasEzhYfOp372p-9s1YLG_kxI,65
kolibri/backend/sklearn/meta/chain_model.py,sha256=PxnxSfJs5Rn_xnXdYIiMju_JLKm2MOjlqxo-T9vN2F0,13254
kolibri/backend/sklearn/meta/ecoc_model.py,sha256=8BzTahcxRWwoyiCE1ZeSAu9QHNa3DGSN7yxWxcaztAg,28328
kolibri/backend/sklearn/meta/ensemble_samplers.py,sha256=DeZnYuubrun2l3JTC_nrTIWmKZarkO8CXAzZkU3E1SM,28316
kolibri/backend/sklearn/meta/multi_output_estimator.py,sha256=r364n66EZd9qRsYeHWlU-hcKwnNuq1lLeVTRtFQ_znc,7645
kolibri/backend/sklearn/meta/ecoc/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/backend/sklearn/meta/ecoc/code_matrix.py,sha256=Ls1UyCt3zI5WMKDSsSJYhwlNmxy7flbNBXX6ExOvDwk,8616
kolibri/backend/sklearn/meta/ecoc/criterion.py,sha256=7HFXDTufc5poIo0F-PnEFxK-tc3wDGvTMYJ09RXrDsA,5551
kolibri/backend/sklearn/meta/ecoc/decoder.py,sha256=tbyglJ-WzNFHCDKRrFS5IDnji8rKsKUqRSyCxs3_iz0,9089
kolibri/backend/sklearn/meta/ecoc/sffs.py,sha256=G9Z2RvEYLTx9zl6EZUfPhfHiB7fgGZRKgxspjzOGULk,3869
kolibri/bin/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/bin/datasets_configs.json,sha256=Kxp26pPdkKw0PMYBP0TrtXGYw76GrCKV3wceLMnYGF8,471
kolibri/bin/kolibri-download.py,sha256=rNBRMaJqGe7CYu7PQ914JPm31KJFdwy86nQijNmXPIE,2731
kolibri/core/__init__.py,sha256=jJ12ejXs61jxKarEIajxM1z8l_S0bK_VhvdKu6KNLMk,45
kolibri/core/component.py,sha256=z7QGQZmSbjgN3LhcqigA96BtfQus1kwgUGkDLAUjgRE,15360
kolibri/core/entity.py,sha256=yZxwmhwauYfjV-XNJ7Oot2VxlkoZACGcpHvetsQfb0E,1111
kolibri/core/modules.py,sha256=ONxqxx2Rj2wmSsGxescFcEkmi6lFOk0BaNAJU2sfIrs,4035
kolibri/core/pipeline.py,sha256=p9knESnZx3-15-qWb2_WC8-Vtcmob2ApokUc-7i4TcU,13141
kolibri/data/__init__.py,sha256=q0Qk6OJ6AZV2-tigCVtRH-Gu0HoB_STLdcwCJ0-aSko,238
kolibri/data/auto_downloader.py,sha256=4Sj3RrDSVIjUduox15o45BJNWpOW_p6DvvoNsjrNSmM,4452
kolibri/data/base_stream.py,sha256=PPW9u8j5MZRi1ImThILOk_j323aDZPuULRbNYki3-Aw,2246
kolibri/data/dataset.py,sha256=OrpruQm7e6UacDY2WEVhg8on7_ySzzIS72WqDLYWsCY,29540
kolibri/data/file_stream.py,sha256=W8x64Tp8xVX2t0h7DDCW67pQ7gK9BTEclpY9DSGk2b0,10372
kolibri/data/iterator.py,sha256=-ymNquPlYE35emY66yGvEUccb91S0bP4emj4CscRfLY,534
kolibri/data/resources.py,sha256=_YBXQXvpEeCHbKAG24FkJsjE4hFX-lVeodFq9tiAGSc,743
kolibri/data/schemes.py,sha256=KzxsSXR0mtvtCKOfXwNMggWGacy6l0850OCbb1wwgZ8,10130
kolibri/data/streams.py,sha256=k1xJjvS8k898DvQ2ysGR9nijKiuHTzx-pj8U6Bx4dGM,5610
kolibri/data/text.py,sha256=XHJKENpOng8Z-qI_AqJe_IXvJtTTHOk-MYJp15mPtJU,7910
kolibri/data/format/__init__.py,sha256=uDK8Bs_c3O4o9znYhK7_huuU5PVF-UnoWmHUOLG8z1w,94
kolibri/data/format/conll.py,sha256=6WoRsOLmh5lJxNqnDu72U1HzBoYjOO3HVz8dHew4Hyo,539
kolibri/data/format/csv.py,sha256=Eh1PAmR0KymT2O91b5tSdz6kazgkYUzDWLQ8L-j2FpY,385
kolibri/datasets/__init__.py,sha256=awAxR-MpCbwZIXUR0d7F3kcLvklSiNdnroKQWDfcGww,47
kolibri/datasets/read_data.py,sha256=uYTPrO7ddvjy47KVc392hz4OyIToNYIGryHxSifm_Lo,2067
kolibri/evaluators/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/evaluators/classifier_evaluator.py,sha256=1t1AjdaGmR33w6xmj-qbH-GuaraH1y7wsa839x8CI8Y,8795
kolibri/evaluators/clustering_evaluator.py,sha256=16otU4Hibi3wJe8cQvV43fXMeY6MFFZ7sJWC1Enz4pU,2489
kolibri/evaluators/model_plot.py,sha256=gdLEoRCNopIzL0ttpaDXjC7UW4Gw9rKixSgd4jK3j40,41682
kolibri/explainers/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/explainers/shap_explainer.py,sha256=F_ULVxCYLbcB7vTnpEwcHp_Wv-FOhBHHzwNBR--I10M,12089
kolibri/features/__init__.py,sha256=h_e9EV5xw_sUmqcUqzrJ2ejKsSHwnn7E64lq7OMX9ec,67
kolibri/features/base_feature.py,sha256=b0LKWapmxIM44vvKYSfTr4nkUPldq25FQU2Or1nbn5o,2781
kolibri/features/basefeaturizer.py,sha256=u3pi5rhtu4CexBWyc_13V-mXWD-n6zqoHShjuxvSow4,1395
kolibri/features/tabular/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/features/tabular/time_serie_featurizer.py,sha256=9d7OXelztf71KiI8rH0B-QoKHs6_w2MYwbppN5pBwGw,1730
kolibri/features/text/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/features/text/tf_idf_featurizer.py,sha256=-dgNAFDkvFBxmKJqO6UabXLU7h4woCX91D4dOVmPg3k,6316
kolibri/features/timeseries/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/features/timeseries/features_utils.py,sha256=hR_KYxqwaJI6x41X2bQ4V-ImE_PZZDY0rAH_wwBoYOg,33656
kolibri/features/timeseries/ts_featurizer.py,sha256=wyD4VP-ogmLVDef4JVE3T8rs0PvCQfp5KjEYiEuo70M,10666
kolibri/features/timeseries/utils.py,sha256=If0kKPpfB67vorgsztehMzDypFmLcNJlFpAQmzBJQIY,7627
kolibri/formers/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/formers/tabular/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/formers/tabular/clustering.py,sha256=b2FCvqtbJtHtxxK_c2Vq-lve5B8jJqpLMk1xb0GhJTg,1043
kolibri/formers/text/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/formers/text/similarity.py,sha256=RZV5Sv1DFL2r2RpGYHDxPZVUt3s8QOFL_7yJQzSM2GE,4501
kolibri/formers/text/topic_former.py,sha256=Pz8paLQ-5ZWcdCgWp080EDbfxh4kBQSO3YaSVx1y3jw,40750
kolibri/indexers/__init__.py,sha256=Yccuyu1fpnxtb6Wkhr2TBaJaFdD7DkgqEDUnauvQYwI,109
kolibri/indexers/base_indexer.py,sha256=hHymN93QhSR4FR43L3qhWtct24ZPst4hwe_KuSEatS0,5175
kolibri/indexers/label_indexer.py,sha256=gSn107t4COe6wiBWPSgyGWMqlIZXPLbmH6vUiJZNLEQ,3325
kolibri/indexers/text_indexer.py,sha256=lQkK6-vuqIQ-pS7WapVI5JGyWxhAYe5lHAI9xooWzSI,5910
kolibri/optimizers/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/optimizers/metric.py,sha256=MUdonc4U_QD30ibtgaRk2bvCmC9P2H2A93zSLiGyeSU,9226
kolibri/optimizers/optuna/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/optimizers/optuna/knn.py,sha256=bUXbMcF1xZ5AEGSs56NJcQ-rfW2pJnZCXtziL3hQr64,1653
kolibri/optimizers/optuna/objective.py,sha256=sHUyJI_XzgJM7PzRVYQ_DX5ujFlbVqRA_NombVHx0Es,6768
kolibri/optimizers/optuna/tuner.py,sha256=QKMlq7I4qs7JqfMfCGjltB3VDGwwi4Q9U7TpTFI4NRU,3596
kolibri/preprocess/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/preprocess/tabular/__init__.py,sha256=CPmIH4BxoSUnpDiponus0-lGOVjBM8wR-Mh-HOQuEkU,1575
kolibri/preprocess/tabular/binning.py,sha256=CS7AEBXSFzSP1uQquLsntaFyIkpnFFus2J8WRJP0BKg,3030
kolibri/preprocess/tabular/boruta_py.py,sha256=9p0KaYupLBKHTp1Snf5iELe5q6YdWoC2Ik3FKHXt5Jg,8728
kolibri/preprocess/tabular/cluster.py,sha256=Rlv4NeDxGMosq-QVZfD1k0Jd_upongJkI9I51qpYzqc,5219
kolibri/preprocess/tabular/data_imputer.py,sha256=3QkLVGKk8CFXFrk9MHuJu6I7XzhlH1gLEAjgGjQldi4,11661
kolibri/preprocess/tabular/dummy_converter.py,sha256=x1mofFqRzA2be7slsl2rTInXH1U4j6-TxEg-cpXxRaY,2968
kolibri/preprocess/tabular/feature_interaction.py,sha256=od9bWyMUpo0mKmSZJQ7vwkehD32wLHvmLIu0HMdeTL8,13108
kolibri/preprocess/tabular/feature_selection.py,sha256=qPai7o5iGK0Cq3fL7z3_7JSZkrpbMy6pMfbtQkEPZic,10163
kolibri/preprocess/tabular/infer_datatype.py,sha256=3XKktpk4OR0yO2IneczH8RdFU86NIgGRy_vpy2powb4,3783
kolibri/preprocess/tabular/multicollinearity.py,sha256=xhoGlcpj_BYOmtZT6Dix7jUdd0LCxPv2RSfOqgm6qSc,13286
kolibri/preprocess/tabular/normalize.py,sha256=UtWyKM9CRcuaYX4qZwHmh0e6-IGEOjGqtu8_UtGaW_Y,2652
kolibri/preprocess/tabular/ordinal_transformer.py,sha256=PLw2ywCwh65pRNGEnJaKnPIfu9cIVTd5k8QMhr1E86o,1620
kolibri/preprocess/tabular/outlier_remover.py,sha256=zspoSa93IdLqH1Dv6ZCjy8BMLCUR7csHbQ22mddU80Y,2584
kolibri/preprocess/tabular/preprocess.py,sha256=LQGoOSQCApNTMaCyPB6pStV1ybp1WpDLspYZ8e4eH80,150117
kolibri/preprocess/tabular/preprocessing_pipeline.py,sha256=TrifhS7lqXZywbatMwtS03mRJXns2PilfOhrGG4Za4w,20172
kolibri/preprocess/tabular/rare_levels.py,sha256=OcP8gmnURLwkAARL933eZJyX_UqNFEYtUWNd5RVSwlc,3432
kolibri/preprocess/tabular/reduce_cardinality.py,sha256=uMKsS0iL9bZFY3FtFOjildUksJen7zyT3jIowA5EFXM,8598
kolibri/preprocess/tabular/reduce_dimensionality.py,sha256=OIUxm9JY3goCb1lgrkwtDFno4_YMkocgGkDTgF5W4Mg,4848
kolibri/preprocess/tabular/regression_target_transformer.py,sha256=EauWaMcIbA6D0daXaF12v8ErZFsuW8exvSzdnIBBniU,1801
kolibri/preprocess/tabular/similar_features.py,sha256=jXynt5mbHiMk1zYEPt-M6wYGg3VTnw2FsOwLGUXP720,2003
kolibri/preprocess/tabular/time_features_extractor.py,sha256=sunqoXHlECNM6zFVEdzCpOsgo8kOtmXv__stz5ct5lM,4003
kolibri/preprocess/tabular/zero_variance_remover.py,sha256=esp7V4lreCZidBme5aWPRFtn7LqpfO_P_JkOCfuuC74,3535
kolibri/preprocess/text/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/preprocess/text/email_cleaner.py,sha256=zbgAU7j4C17YxwC60BJ-hYT-Xna9kYunfsbCx3xqTJ8,1854
kolibri/preprocess/text/cleaning/__email_configs.py,sha256=V1duGT_BLPhyhlpKumSttPldtpDowZP-PK2rhN6MxLk,4133
kolibri/preprocess/text/cleaning/__init__.py,sha256=41XUW4heGY_GuytXG6wyxAq1Zc-YPekqmw7VrrCDFqg,67
kolibri/preprocess/text/cleaning/cleaning_scripts.py,sha256=F-43ksMP35iZ-f5xQC7407P_WPmToMPoE3j05aihZkM,1129
kolibri/preprocess/text/cleaning/email2text.py,sha256=igiINwwrPVFGuocbmRaGOskdTiJ6vuicCPEmzL89n10,18624
kolibri/preprocess/text/language_detection/__init__.py,sha256=erG9ZLwf8735lWLBYp3gnfTqS8HWVabsVVgeLDNvsy0,82
kolibri/preprocess/text/language_detection/lang_detect.py,sha256=DtrTrkh17UI2A0ZKCUDylxW7L13p1j6wy3sYdw5J0Qc,1668
kolibri/preprocess/text/translation/Translate_.py,sha256=jB7Nwka0SW1wvN0KryIZIJOHnQKBnZyxCSmSr2m_2mk,7047
kolibri/preprocess/text/translation/__init__.py,sha256=WRb9MqHA1lNoWO7lFYuHB7bMZysgOek_pOxZW8o6-QU,1079
kolibri/preprocess/text/translation/client.py,sha256=EBiyHGbs3hm48wGJYyAE4_HAmmJ2hJZ0Xfp6z9Z_xmA,9893
kolibri/preprocess/text/translation/constants.py,sha256=qQ5ANUGmVkTIaJsW8AyxcfDw9J8qYgbe4gGrvWZAlcQ,9746
kolibri/preprocess/text/translation/models.py,sha256=zNBDehv23u0hOCOSB7bI2ua0k_H1KoST574TpzoeeV0,1601
kolibri/preprocess/text/translation/translate.py,sha256=55zQbGZyx-l4UVVVS_q0p1V40JSSL8U3n2qA-_9qdYY,6262
kolibri/preprocess/text/translation/utils.py,sha256=Vt_iwckxPP4QprnScc3bo3nA_ldpH7I9YJtTdtnfyLc,2640
kolibri/preprocess/timeseries/__init__.py,sha256=1e4qvaiog7L8InRf96O_lirDnfm_X0uuQujFvlFkaPY,65
kolibri/preprocess/timeseries/window.py,sha256=vlBUoFaXpG7QiydtW1X5RXSM9J4KszTVmZpvhTu8bUA,2866
kolibri/samplers/__init__.py,sha256=lzKBX2_t8UIHR9Vfe4ldAyH4tpVDgA7-yFhKrJ9QxsQ,2014
kolibri/samplers/auto_smpler.py,sha256=BTKAOuhBPluY_7jE-GH-uSlPJFhaZR91K5BRXwz_Aso,5095
kolibri/stopwords/__init__.py,sha256=Tf5aza_sJkBdVAZOrYZd8N6R_Mk_8uy2UhoMnpm5NRQ,52
kolibri/stopwords/stp_wrd.py,sha256=SqVwHu73L1bIw_EpTjoPbjFPWRK5wQpcokPJn2OdnP0,2338
kolibri/task/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/task/tabular/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/task/tabular/anomaly/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/task/tabular/anomaly/anomaly_estimator.py,sha256=SYXOFU2EFPN5ailqoeymuLw6S-LVuuWJph-wxGeBh98,1469
kolibri/task/tabular/clustering/__init__.py,sha256=tGKCWNXTceLGjxO76Wg8WbO2DYZQiUexAQPhxvtwqK0,74
kolibri/task/tabular/clustering/clustering.py,sha256=MzzewLYtIkl9OxcwL3AQW58t3GDSL6MUw6uuXbBg9qA,4376
kolibri/task/tabular/regression/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/task/tabular/rulemining/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/task/tabular/rulemining/association_rules.py,sha256=_9mMxCmc8f6J6Cr_532xNVbtgVNVuTRJ_EMQTR8AgEY,9912
kolibri/task/text/__init__.py,sha256=bBKkL8YGqAVNsX848UYguJf8pxEsincNVey9WOjXskg,44
kolibri/task/text/classification/__init__.py,sha256=B5-nvifCK4aV5HqoIg0f8ZaDmahRUDfTt_wkd-xbc5M,79
kolibri/task/text/classification/sklearn_estimator.py,sha256=wMBqMU3ay_LQ10aMjhJRflv5s71x_mzcyNeI9iQ5MnE,3407
kolibri/task/text/entities/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/task/text/entities/common_reg_extractor.py,sha256=w7x9Tnxdn5gjjFh20cFbh4ETckvjLO2vbczmos6TrDo,6708
kolibri/task/text/entities/crf_entity_extractor.py,sha256=fRLiLvrbTUOyL2Bw9NKsC3pXsdd8w6HIoo-vFRzFU88,18309
kolibri/task/text/entities/dictionaryExtractor.py,sha256=j8td9mUO2MrOMsLUj82NEuCxo1U-XIestorFcLzDM6Y,1011
kolibri/task/text/entities/entity_extractor.py,sha256=otn44g8u3A7eG2b_IiWnTAwMzPjSefq5m_2vL4b7GCY,3003
kolibri/task/text/entities/entity_synonyms.py,sha256=gDV7Tn8FFs_Rk6K8Lavy2r3JpyeRTBuEvF_wfOXHvsk,4343
kolibri/task/text/entities/person_extractor.py,sha256=xz3Zjhh-MqYG9nXTNvgpa_31mRz7GcDhnwWn232LaI0,3234
kolibri/task/text/entities/preprocessing.py,sha256=CsKkBhy116JAHrEPFdPSdvWX2X2iXeSF6eJvFUC3_3c,2295
kolibri/task/text/entities/regex_extractor.py,sha256=-x11jf6gkHoq-kF3BWh8pYh9BpBOxj1r1x_pMThqxoM,2644
kolibri/task/text/entities/templated_extractor.py,sha256=WgbKhiF2KVcv1uMaXvSx6YCVnDVvcuVrsOkxJJfghuY,6418
kolibri/task/text/intents/__init__.py,sha256=fDcNlTbX0Nag981_mCZpKs2T5PsFukb3tjC4eXQDQ9M,5
kolibri/task/text/intents/intent_expressions.py,sha256=gepMxVzBHQjO0NRKsHXWILIiUKkzKLnzHK2_LogGMvk,3927
kolibri/task/text/intents/domains/__init__.py,sha256=TgjpTJEoYunCeX6jh-j8mDkJ9NwTZtdK9T61C1Sf3D0,1422
kolibri/task/text/topics/__init__.py,sha256=g0CWthZqZr8Jvi6DAV-3a9NXg6RqK9uQbLsjXdNHskE,152
kolibri/task/text/topics/baseTopic.py,sha256=Z50oDVDTBgmlVh6Dxm5JaseWbiD5VvdPGorayrlg9Ws,3558
kolibri/task/text/topics/mallet.py,sha256=OR-Nis9COWqWVAX2C5Z7I-i1hJ2s1usK_GFKF6auJTs,24844
kolibri/task/text/topics/topics_estimator.py,sha256=GuWWe7gt9gdRajLHGRjYCc2hNZXmxhnXUJ5rWZggOl4,14954
kolibri/task/timeseries/__init__.py,sha256=2q2W_Du5Flox9oLOSqUE6po3mjDyrp_Y1IA3s_hjgjI,58
kolibri/task/timeseries/dataset.py,sha256=SopVhuGnXX0OuNILeFqjbOO-ZlXH5auEse_tIcdKxy0,23741
kolibri/task/timeseries/metrics.py,sha256=AI2XbadyMJtwbaUim_PC_t9k3wTBzPU5XNjBjFW_y_A,962
kolibri/task/timeseries/analysis/__init__.py,sha256=zOksgvFRNNecU-z6b7Tis-VrfrKN9WtEzDDieFSvsoc,1953
kolibri/task/timeseries/analysis/eda_utils.py,sha256=-lw3DwnlJULpoVnVdB1CVOJ3C5rRG_Maauvy2aKxdN8,7234
kolibri/task/timeseries/analysis/plotters.py,sha256=SksGv_601b8_I8MeRGvvsMh1k_pjbg3xrocqNBqhqQs,17003
kolibri/task/timeseries/analysis/feature_relevance/__init__.py,sha256=76trWBGCXCiAlSx8u9ggfn3ELHHBeEFmiklMosqb5ag,494
kolibri/task/timeseries/analysis/feature_relevance/relevance.py,sha256=o24M-RxsePRRqATGEmDW0TigW9_YXVkvp-sRO9OjYQo,3066
kolibri/task/timeseries/analysis/feature_relevance/relevance_table.py,sha256=VvtAdg0v5QlqnKCtSIuZs5FQgX3P7IhdKsyxhozVmtE,2919
kolibri/task/timeseries/analysis/outliers/__init__.py,sha256=KXxUdUXCOAey8kkK_CZpdYcsqjbt5HEMs_mI7Wb-bK0,583
kolibri/task/timeseries/analysis/outliers/density_outliers.py,sha256=NLjzCKwrDvIUS5Y1hh7Bd74bu48Ok4BJ57E67c6mAU8,5017
kolibri/task/timeseries/analysis/outliers/hist_outliers.py,sha256=lRVmbNYAvSjTmYKbiKXFFHZb4w2DDryrRU9_JiHKQsE,13178
kolibri/task/timeseries/analysis/outliers/median_outliers.py,sha256=LOIVmtYKezbFcfM0gZqztPqEx56sWy7O0gDgyeeyg5A,1878
kolibri/task/timeseries/analysis/outliers/prediction_interval_outliers.py,sha256=Kap9gxlRsKKyxoHqwsd74RBN9f1XO3YFr7cMlyF21XU,2998
kolibri/task/timeseries/analysis/outliers/sequence_outliers.py,sha256=PiaW43p09ATc0P9dYIEKztiIqQoP2bw3q60YnHEJlPQ,3501
kolibri/tokenizers/__init__.py,sha256=wtQmlG4jWyxK_AbteTlkguK-u6f_GZYMb7mVVEO_0fQ,316
kolibri/tokenizers/char_tokenizer.py,sha256=zM69ULzwTcVAYu3VGrYnsvoL_OSTIW8e4qYgysfLIfY,4069
kolibri/tokenizers/kolibri_tokenizer.py,sha256=AReu6CLFx7vEtGggKL2M9WoabejCpslUwDSl6ftZU1Y,5785
kolibri/tokenizers/regex_tokenizer.py,sha256=EU7ZXGasuRoYbseAmFNQ355Pypgln0k0J2uzdpn9gGk,2773
kolibri/tokenizers/sentence_tokenizer.py,sha256=xSQf4EMAABFYcpsnecc_yj_zJwRExCQDoo_QUXFxzHM,1110
kolibri/tokenizers/tokenizer.py,sha256=J15NENc-aZi19oXvtQXgITOp7BJdK1fgOQAhS6x5aZA,2264
kolibri/tokenizers/word_tokenizer.py,sha256=80TyOzZmFEzEAYdfsLCFZZJtEWF3fMrKZRxp1xqCdJE,2461
kolibri/tools/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/tools/_regex.py,sha256=4xOVvbQMT7mF4Lk8VbaBQ1jxovHd8irZMfT-4BdnDhM,411
kolibri/tools/gebbrisg_detector.py,sha256=P93bR1lQwM6YM7btNoFXzwg7pQEw44MThj9zaZ2ldGk,2063
kolibri/tools/keywords.py,sha256=S-aObU6a_m-YLqWvja_qkcfOSrRXpWmpYIPK7nRmMp8,25525
kolibri/tools/regexes.py,sha256=wjOdIYre0YH5B6iJRQaR-xBBgDdoBejo4JOw1ST4CaQ,1694
kolibri/tools/scanner.py,sha256=PEmdkD3mOJi3ira-oT3P2envt07s8cMIzLJbTkkbdoQ,16332
kolibri/tools/word_frequencies.py,sha256=Y28YsOQ9HzEmiAtZK_LfST-IZFm6Vm5ky_eLTI3_Li0,13151
kolibri/utils/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
kolibri/utils/common.py,sha256=oLZpKglqEkPtT3E8ZsCo8B4mHSdAmeejwzylFphdfuc,5802
kolibri/utils/language_info.py,sha256=MxLTC_9odTRgNKDgN_w4mrMEYuWyfih_dxwGTwAUW64,3259
kolibri/utils/matrix.py,sha256=8N-2XU398bUxonr7n2vlST9mXe4qEFYCVAGTEWH56Jg,2904
kolibri/utils/parallel.py,sha256=da-WNpIKjaqqprIQmiWHDqjG1fa5ZXKv8K4SEDcqPDA,631
tests/__init__.py,sha256=cLEG0Ty3GCvE16djVZjDu8rlBEUAVjwMZXa9fQlxVt0,52
tests/test_pipeline.py,sha256=BhvJX-IqJ_5EWnVj-VfXiM2LzR3-y9DGf3hZEaxEs50,960
tests/utils.py,sha256=vvK537soXHoQnfBgTZw7yAtUjMO0pUWSSLcy8fH1pEg,557
tests/entities/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
tests/entities/test.py,sha256=KmyrZiq52x4rE5gmX3o_5tXDnqwJzihazIYWEr179-g,7812
tests/optuna/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
tests/optuna/test_optuna.py,sha256=AbpHGcgLb-kRsJGnwFEktk7uzpZOCcBY74-YBdrKVGs,1
kolibri_ml-1.0.57.dist-info/LICENCE.txt,sha256=eKw0ToK5-JtbuPy1tofBiXFxGgk1zhq5x0mB7gnTxc8,34572
kolibri_ml-1.0.57.dist-info/METADATA,sha256=KxBXJcwgOE8nOh6WcC5yOyDuz8ktBWrjz6YLryDNUoU,3940
kolibri_ml-1.0.57.dist-info/WHEEL,sha256=OqRkF0eY5GHssMorFjlbTIq072vpHpF60fIQA6lS9xA,92
kolibri_ml-1.0.57.dist-info/top_level.txt,sha256=NGm7zB2Kg42u_WsPHekrdCFra8GwnSQ0VZjOkTOupu0,24
kolibri_ml-1.0.57.dist-info/RECORD,,
