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Add THX SSN hash parsing
2026-05-21 13:31:48 -04:00
.gitea/workflows
Add initial files
2025-01-17 16:20:44 +00:00
block.py
Add THX SSN hash parsing
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category_orders_train_M1.json
Sync m-1-v-1 block with local updates
2025-11-23 23:22:32 -05:00
category_orders_train_M2.json
Sync m-1-v-1 block with local updates
2025-11-23 23:22:32 -05:00
category_orders_train.json
Advanced M series V1 model block
2025-03-12 16:12:18 +00:00
Dockerfile
Add initial files
2025-01-17 16:20:44 +00:00
isotonic_model_M2.joblib
Sync m-1-v-1 block with local updates
2025-11-23 23:22:32 -05:00
latitute_longitute_reference.csv
Add digital_id_confidence_rating dtype, split prepare for M1/M2, clean lat/long CSV
2025-11-25 05:58:44 -05:00
post_processing.py
Sync m-1-v-1 block with local updates
2025-11-23 23:22:32 -05:00
pre_processing.py
Add THX SSN hash parsing
2026-05-21 13:31:48 -04:00
processing.py
Add digital_id_confidence_rating dtype, split prepare for M1/M2, clean lat/long CSV
2025-11-25 05:58:44 -05:00
README.md
Advanced M series V1 model block
2025-03-12 16:12:18 +00:00
request_schema.json
Add input IP parsing
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requirements.txt
Sync m-1-v-1 block with local updates
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response_schema.json
Add THX SSN hash parsing
2026-05-21 13:31:48 -04:00
test_block.py
Add THX SSN hash parsing
2026-05-21 13:31:48 -04:00
xgboost_model_M1.joblib
Sync m-1-v-1 block with local updates
2025-11-23 23:22:32 -05:00
xgboost_model_M2.joblib
Sync m-1-v-1 block with local updates
2025-11-23 23:22:32 -05:00
xgboost_model.joblib
Advanced M series V1 model block
2025-03-12 16:12:18 +00:00

README.md

Advanced M series V1 model block

M Series Model trained on historical data to identify fraudulent patterns.

Description
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Readme
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Python 41%