feature_segmented_histogram_binning_calibration
Summary: We implement a hierarchical fine grained binning structure, with the top level corresponding to different feature segments and bottom level corresponding to different range of ECTR. The model is designed to be general enough to perform segmented calibration on any useful feature
Test Plan:
buck test dper3/dper3/modules/calibration/tests:calibration_test -- test_histogram_binning_calibration_by_feature
buck test dper3/dper3_models/ads_ranking/model_impl/mtml/tests:mtml_lib_test -- test_multi_label_dependent_task_with_histogram_binning_calibration_by_feature
e2e test:
buck test dper3/dper3_models/ads_ranking/tests:model_paradigm_e2e_tests -- test_sparse_nn_histogram_binning_calibration_by_feature
buck test dper3/dper3_models/ads_ranking/tests:model_paradigm_e2e_tests -- test_mtml_with_dependent_task_histogram_binning_calibration_by_feature
All tests passed
Canary packages:
Backend -> aml.dper2.canary:e0cd05ac9b9e4797a94e930426d76d18
Frontend -> ads_dper3.canary:55819413dd0f4aa1a47362e7869f6b1f
Test FBL jobs:
**SparseNN**
ctr mbl feed
f255676727
inline cvr
f255677216
**MTML regular task**
offsite cvr
f255676719
**MTML dependent task**
mobile cvr
f255677551
**DSNN for AI models**
ai oc
f255730905
**MIMO for both AI DSNN part and AF SNN part**
mimo ig
f255683062
Reviewed By: zhongyx12
Differential Revision: D25043060
fbshipit-source-id: 8237cad41db66a09412beb301bc45231e1444d6b
