SIENTIAPDE-1430: Introduce comprehensive integration testing with JSON-based scenarios and detailed README documentation. Enhance training workflow to support advanced model configurations, including polynomial regression with mandatory scaler validation. Ensure robust prediction handling by calculating training predictions (y_train_pred) before denormalization and automatically configuring datetime indices for time-series operations.

2025-12-18 17:05:10 -03:00
parent 6e8f87b2a3
commit 06fd08dc70
18 changed files with 631 additions and 37 deletions
--- a/docs/test-scenarios/10-linear-regression-with-ar.json
+++ b/docs/test-scenarios/10-linear-regression-with-ar.json
@@ -0,0 +1,28 @@
+{
+  "_description": "Regressão linear com variável autoregressiva (AR)",
+  "experimentName": "test-linear-with-ar",
+  "username": "bruno.domingues@aignosi.com.br",
+  "modelName": "Linear Regression",
+  "targetVariable": "03CV020/CORRENTE_N_M1_PV(Value)",
+  "variableColumns": ["303-WIT-200(Value)"],
+  "lagTrain": {"303-WIT-200(Value)": 0},
+  "lagVal": {"303-WIT-200(Value)": 0},
+  "remStaticWin": false,
+  "lowLim": {},
+  "uppLim": {},
+  "window": 0,
+  "useScaler": false,
+  "includeAr": true,
+  "trainSize": 80,
+  "shuffle": true,
+  "lineSeparator": ",",
+  "decimalSeparator": ".",
+  "removedIntervals": [],
+  "degree": 1,
+  "interactionOnly": false,
+  "nanTreatment": "drop",
+  "startDate": null,
+  "endDate": null,
+  "scalerName": "None",
+  "supportFilters": {}
+}