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Browse files- __pycache__/inference.cpython-312.pyc +0 -0
- config.json +45 -34
- encoders.joblib +2 -2
- feature_importances.json +13 -15
- model.joblib +2 -2
__pycache__/inference.cpython-312.pyc
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config.json
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{
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"model_type": "
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"
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"features": [
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"month",
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"day_of_week",
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"is_weekend",
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"country_encoded",
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"category_encoded",
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"temperature",
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"is_ramadan",
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"ramadan_week",
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"is_eid_fitr",
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"is_eid_adha",
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"electronics_media",
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"fashion_apparel",
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"food_dining",
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"groceries_fmcg",
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"health_wellness",
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"home_furniture",
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"jewelry_watches",
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"luxury_goods",
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"sports_outdoor",
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"toys_kids",
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"travel_entertainment"
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],
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"countries": [
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"Bahrain",
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"Qatar",
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"UAE"
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],
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"metrics": {
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"
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"rmse":
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"mae":
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},
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}
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{
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"model_type": "GradientBoostingRegressor",
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"feature_columns": [
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"is_ramadan",
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"ramadan_week",
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"days_to_eid",
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"is_eid_fitr",
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"is_eid_adha",
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"is_hajj_season",
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"country_encoded",
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"category_encoded",
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"temperature",
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"day_of_week",
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"month",
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"hijri_month",
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"hijri_day"
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],
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"countries": [
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"Bahrain",
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"Qatar",
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"UAE"
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],
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"categories": [
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"dates_sweets",
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"electronics",
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"fashion_abayas",
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"gifts",
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"groceries",
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"perfumes_oud"
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],
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"metrics": {
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"mse": 24.44782802085175,
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"rmse": 4.944474493902436,
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"mae": 3.8228789470187383,
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"r2_score": 0.905699037541998
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},
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"description": "GCC Ramadan Retail Demand Forecasting Model",
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"input_features": {
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"is_ramadan": "Boolean (0/1) - Whether it is Ramadan",
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"ramadan_week": "Integer (0-5) - Week of Ramadan (0 if not Ramadan)",
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"days_to_eid": "Integer (-1 to 30) - Days until Eid (-1 if not applicable)",
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"is_eid_fitr": "Boolean (0/1) - Whether it is Eid al-Fitr",
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"is_eid_adha": "Boolean (0/1) - Whether it is Eid al-Adha",
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"is_hajj_season": "Boolean (0/1) - Whether it is Hajj season",
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"country": "String - One of: UAE, KSA, Qatar, Kuwait, Bahrain, Oman",
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"category": "String - Product category",
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"temperature": "Float - Temperature in Celsius",
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"day_of_week": "Integer (0-6) - Day of week",
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"month": "Integer (1-12) - Gregorian month",
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"hijri_month": "Integer (1-12) - Hijri month",
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"hijri_day": "Integer (1-30) - Hijri day"
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},
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"version": "2.1.0",
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"output": "demand_index - Predicted retail demand index",
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"changelog": {
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"2.1.0": "Retrained with Hijri features and temporal split. R2=0.906 (honest). days_to_eid=29% importance.",
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"2.0.0": "Initial deploy. Random split inflated R2 to 0.992. Missing Hijri features."
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}
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}
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encoders.joblib
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version https://git-lfs.github.com/spec/v1
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size
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oid sha256:da84e6211fe94a186197f3850a18bf6c3aae1f58360000a75f8590b8c5a2cc0a
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size 850
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feature_importances.json
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"month": 0.001135660451836884,
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"day_of_week": 0.0005715535953640938
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}
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{
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"is_ramadan": 3.69275253834204e-05,
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"ramadan_week": 0.003525943796247472,
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"days_to_eid": 0.29290416306240935,
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"is_eid_fitr": 0.0010144082359060686,
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"is_eid_adha": 0.0012917867230512092,
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"is_hajj_season": 0.10161264627734466,
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"country_encoded": 0.11934693744055763,
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"category_encoded": 0.3920205132356218,
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"temperature": 0.022141510058809637,
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"day_of_week": 0.0418962978935297,
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"month": 0.02049986667570955,
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"hijri_month": 0.00037238780289487874,
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"hijri_day": 0.0033366112725345945
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}
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model.joblib
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 1760473
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