langfair/__init__.py,sha256=gQc7r7g5Ml14ZajnknlkknShwf3p814tTd9vwqfdzfc,684
langfair/auto/__init__.py,sha256=zNI7s20lVrYUF6CqdLebTRcUSrAW8TUhWKMSh28nn5M,668
langfair/auto/auto.py,sha256=WdGU4W2Dsa9l0BV_mq1FaX-3CGtCflG2uvZMg_PBYCo,15985
langfair/constants/__init__.py,sha256=C81byTuwlZNN0yDITp-awmBXiwOvt_KFBvzVAPU71Qs,603
langfair/constants/cost_data.py,sha256=uwGXg3RpX5gVRRVT8K07TBv6UIXwKxq6MXvA0V2_Nto,1890
langfair/constants/word_lists.py,sha256=lR8TP3ssF3ohijBUXW1-J-7Dy3JRWIIOJFv6ej0w3wg,16860
langfair/generator/__init__.py,sha256=Qvh9pmZ3vOG6fQ2qERdkaHU3tP0LgXJVWSNoGV_DAMk,804
langfair/generator/counterfactual.py,sha256=-l8thbOHOjVt7rjHodIB2CV2FkBErglc_sfWzbsgGYw,19754
langfair/generator/generator.py,sha256=rKlJWfP2zmJ57Cg_fYz1qHudliHhHjKVqzM9ouvrH-Y,16734
langfair/metrics/__init__.py,sha256=C81byTuwlZNN0yDITp-awmBXiwOvt_KFBvzVAPU71Qs,603
langfair/metrics/classification/__init__.py,sha256=QMbNjvLzBhDVA4aARS3fbRzTOkE7w5CAzyis06WmSiY,722
langfair/metrics/classification/classification.py,sha256=--ZZNIzDV6RVQtSB0ByoNbQPtAdqQIEtiWJExpEAUHE,3315
langfair/metrics/classification/metrics/__init__.py,sha256=xjAY26B7rXTrCbpNCC_WaUFhgCq7S0ecNX6MduC1wd8,1295
langfair/metrics/classification/metrics/baseclass/__init__.py,sha256=79d_9RTlI_NfwHgKmFY69zVvGjBdA7Pn_0zU0MPAD7Y,703
langfair/metrics/classification/metrics/baseclass/metrics.py,sha256=q2I-7NiQ67P_uBZq_BQ401kV7FhtvvmfAYIUn7stZtI,1191
langfair/metrics/classification/metrics/false_discovery.py,sha256=gs_dsOM4fQv_ITq2jdXATyJ8h6TBuDqGm0jjv_SMqSc,3064
langfair/metrics/classification/metrics/false_negative.py,sha256=fgCw5JrG3J5qyGwGiCjCZkZadIGiqbQ8ftr-FtfpQ7s,3197
langfair/metrics/classification/metrics/false_omission.py,sha256=10TJvF8P1z3YJxlGHKTZk3AGuAj42JjxMer18A5UBw0,3202
langfair/metrics/classification/metrics/false_positive.py,sha256=vdXkwXWXBoiEpVC030Vl1-hf1g7jTaH9tCOeAvA4QX0,3197
langfair/metrics/classification/metrics/predicted_prevalence.py,sha256=W81jeYxAhPtm6NegmS2EWymC1ezkahHi9Dqz5LVhKL4,2414
langfair/metrics/counterfactual/__init__.py,sha256=_ZSTWAkfNz0k_Rdc7XN1qQHTUQLU-1O6t7vAo2Wir5o,722
langfair/metrics/counterfactual/counterfactual.py,sha256=MUY4yqrs0gO5jI8aJHJvTAzhfZ99R4vb1O40vLaCoc4,4947
langfair/metrics/counterfactual/metrics/__init__.py,sha256=9SuPVMkSpDZZ-FRghZNdlM8J4_lujPVAdQT8YlQbvuU,995
langfair/metrics/counterfactual/metrics/baseclass/__init__.py,sha256=KPqMP_EMhv4KST1sS9Eox-y5lFzpkDirpv-llocmtqA,703
langfair/metrics/counterfactual/metrics/baseclass/metrics.py,sha256=E3sRCTCWAv6658Kf0nTXcxJcAg38eD5cZPlPfxl7ZsQ,1088
langfair/metrics/counterfactual/metrics/bleu.py,sha256=J-Zrfpve2j9HGxecjbpfnHVgCjK1c7vFcGbunHrWy8Q,3284
langfair/metrics/counterfactual/metrics/cosine.py,sha256=gZKKq_-BejZ-aaO-CEqr6Lf97d_ls0H1UTnWREOjde0,4442
langfair/metrics/counterfactual/metrics/rougel.py,sha256=4Yr_YU9PKNM6F4ZjqADkNmJG5Rrzh5V6_txNgP4OssE,3239
langfair/metrics/counterfactual/metrics/sentimentbias.py,sha256=o_8PYwrwUH1vBfzamNshPEPwI5RhkomuRWdT9fd7Psk,5786
langfair/metrics/recommendation/__init__.py,sha256=8jzxbcuRAKi8Qv5eUk_t2ijZl9EOx7w-CNbNfB9gFMU,722
langfair/metrics/recommendation/metrics/__init__.py,sha256=NSOtCf_6d97t1crP480NeDMrSxCJSZpCrmYpHX_ieGQ,855
langfair/metrics/recommendation/metrics/baseclass/__init__.py,sha256=jevQq3H9nYvXfD1kBdxOvr8u_wHbJxsp9wLpZbS1H2A,703
langfair/metrics/recommendation/metrics/baseclass/metrics.py,sha256=IVecvaLuaP5PSWSZkCt0NAvzhdgoGFqdug8o9kEURB0,1045
langfair/metrics/recommendation/metrics/jaccard.py,sha256=hy3vcPPFgBfyiYaPHxxBSI1wcrl1_pGFbFJZBmkpjeo,1473
langfair/metrics/recommendation/metrics/prag.py,sha256=9Z4CFvkiea1sLYsaF-fYLgOHcQ2-bZ4XD4sKtJ8J0zw,1938
langfair/metrics/recommendation/metrics/serp.py,sha256=aor056E30umoDvC6eWv9_UDAQhbWd7dUYTfkwi1StoQ,1581
langfair/metrics/recommendation/recommendation.py,sha256=u4H4EzaxX-PjUhIQLREt6dWG-KUu3IkQcJXZ7gw1C4Q,12246
langfair/metrics/stereotype/__init__.py,sha256=9_53zQf3miL4m8owbEl9yte_g_rdAjgfX4YYp8NM8OY,706
langfair/metrics/stereotype/metrics/__init__.py,sha256=XUHQfRMx8L1tYTqAhRTwbPfSka0pZddyk7ahKEZdgm8,961
langfair/metrics/stereotype/metrics/associations.py,sha256=mw5itfYWzlXJKzhKYSJJ6dbhC7JSyQSzz0_VSZIawUs,9342
langfair/metrics/stereotype/metrics/baseclass/__init__.py,sha256=4AC1CJveKXoqckkz1_GJ8xG-vYzqOYtYUOkYEMeFivg,699
langfair/metrics/stereotype/metrics/baseclass/metrics.py,sha256=MXkMgxIf77fMMGOG15WblaipUhsxzEUKZkNafn2WXB4,994
langfair/metrics/stereotype/metrics/classifier.py,sha256=2d1zLY-9MFoWeoraN87sHMDaexcS7eFSDFiCLpXvqCk,7906
langfair/metrics/stereotype/metrics/cooccurrence.py,sha256=edCYS53is-O9qETIzD3Ry8XYZIgLw8bjr49GgCwLsFU,11629
langfair/metrics/stereotype/stereotype.py,sha256=bl9BXwO_3GIZ_8H_jT9mv1Ww0Pb8erK2DMrFUOO6cSI,4715
langfair/metrics/toxicity/__init__.py,sha256=TiOap0PM9sb25DFGlSi7W-QHz0wbsdaRVD39r7JCwzY,803
langfair/metrics/toxicity/toxicity.py,sha256=GE2ThTATufgEeQIEqTnYcT-WWFW4-SzirYjPgGe3rIk,11200
langfair/metrics/utils/classifier_metrics/__init__.py,sha256=1vV5cZ4wVo5rWcgcr-ZbXSN77pRjj4EwhaUgEQaIAd0,898
langfair/metrics/utils/classifier_metrics/baseclass/__init__.py,sha256=RnJz271ggBR3w4lWSnPId-dA4kGKP4u-Avjrm3g_Pms,705
langfair/metrics/utils/classifier_metrics/baseclass/metrics.py,sha256=bmpxrPOkbrAfAkQu3_bFG5QhxIXJlHUtgn4Ms_9r3Ng,2075
langfair/metrics/utils/classifier_metrics/expectedmaximum.py,sha256=Xx6rCVzzhYI1IlGVU1zhfX16hxzmNcAAC_sS6dZvG2k,1471
langfair/metrics/utils/classifier_metrics/fraction.py,sha256=vbrDto1MiEal9YKg6-hEGi_jaSNBuN2F0GLiu2kzyHM,1487
langfair/metrics/utils/classifier_metrics/probability.py,sha256=zhDXJGXxrmpuqwzJx_XeyZLKNZ0qmkMTuHulfUI_hVs,1490
langfair-0.1.0.dist-info/LICENSE,sha256=W6CZN3A2CFNAWZz0PjkNUAnmXzDuUfamdM1VI8vN_7Y,11569
langfair-0.1.0.dist-info/METADATA,sha256=jvuEBMCvQTvnWXNNPfE09ZCfhvXaOLAOndRVn3JB_g4,13449
langfair-0.1.0.dist-info/WHEEL,sha256=Nq82e9rUAnEjt98J6MlVmMCZb-t9cYE2Ir1kpBmnWfs,88
langfair-0.1.0.dist-info/RECORD,,
