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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.

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Bruno Domingues
2025-12-18 17:05:10 -03:00
parent 6e8f87b2a3
commit 06fd08dc70
18 changed files with 631 additions and 37 deletions
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28
docs/test-scenarios/01-linear-regression-basic.json Normal file
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{
"_description": "Cenário básico de regressão linear sem scaler",
"experimentName": "test-linear-regression-basic",
"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": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 1,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "None",
"supportFilters": {}
}

28
docs/test-scenarios/02-linear-regression-with-scaler.json Normal file
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{
"_description": "Regressão linear com Standard Scaler habilitado",
"experimentName": "test-linear-regression-scaler",
"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": true,
"includeAr": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 1,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "Standard Scaler",
"supportFilters": {}
}

28
docs/test-scenarios/03-polynomial-regression-degree2.json Normal file
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{
"_description": "Regressão polinomial de grau 2 com scaler (obrigatório para evitar overflow)",
"experimentName": "test-polynomial-degree2",
"username": "bruno.domingues@aignosi.com.br",
"modelName": "Polynomial 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": true,
"includeAr": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 2,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "Standard Scaler",
"supportFilters": {}
}

28
docs/test-scenarios/04-polynomial-regression-degree3.json Normal file
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{
"_description": "Regressão polinomial de grau 3 com scaler",
"experimentName": "test-polynomial-degree3",
"username": "bruno.domingues@aignosi.com.br",
"modelName": "Polynomial 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": true,
"includeAr": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 3,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "Standard Scaler",
"supportFilters": {}
}

28
docs/test-scenarios/05-linear-regression-with-lags.json Normal file
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{
"_description": "Regressão linear com lags de treino e validação",
"experimentName": "test-linear-with-lags",
"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)": 5},
"lagVal": {"303-WIT-200(Value)": 3},
"remStaticWin": false,
"lowLim": {},
"uppLim": {},
"window": 0,
"useScaler": false,
"includeAr": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 1,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "None",
"supportFilters": {}
}

28
docs/test-scenarios/06-linear-regression-nan-interpolation.json Normal file
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{
"_description": "Regressão linear com tratamento de NaN por interpolação linear",
"experimentName": "test-linear-nan-interpolation",
"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": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 1,
"interactionOnly": false,
"nanTreatment": "linear interpolation",
"startDate": null,
"endDate": null,
"scalerName": "None",
"supportFilters": {}
}

28
docs/test-scenarios/07-linear-regression-static-window-removal.json Normal file
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{
"_description": "Regressão linear com remoção de janelas estáticas",
"experimentName": "test-linear-static-removal",
"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": true,
"lowLim": {},
"uppLim": {},
"window": 10,
"useScaler": false,
"includeAr": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 1,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "None",
"supportFilters": {}
}

28
docs/test-scenarios/08-linear-regression-with-limits.json Normal file
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{
"_description": "Regressão linear com limites inferior e superior para variáveis",
"experimentName": "test-linear-with-limits",
"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": {"303-WIT-200(Value)": 0.0},
"uppLim": {"303-WIT-200(Value)": 1000.0},
"window": 0,
"useScaler": false,
"includeAr": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 1,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "None",
"supportFilters": {}
}

28
docs/test-scenarios/09-polynomial-degree2-with-scaler-and-lags.json Normal file
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{
"_description": "Cenário completo: regressão polinomial grau 2 com scaler e lags",
"experimentName": "test-polynomial-complete",
"username": "bruno.domingues@aignosi.com.br",
"modelName": "Polynomial Regression",
"targetVariable": "03CV020/CORRENTE_N_M1_PV(Value)",
"variableColumns": ["303-WIT-200(Value)"],
"lagTrain": {"303-WIT-200(Value)": 3},
"lagVal": {"303-WIT-200(Value)": 2},
"remStaticWin": false,
"lowLim": {},
"uppLim": {},
"window": 0,
"useScaler": true,
"includeAr": false,
"trainSize": 80,
"shuffle": true,
"lineSeparator": ",",
"decimalSeparator": ".",
"removedIntervals": [],
"degree": 2,
"interactionOnly": false,
"nanTreatment": "drop",
"startDate": null,
"endDate": null,
"scalerName": "Standard Scaler",
"supportFilters": {}
}

28
docs/test-scenarios/10-linear-regression-with-ar.json Normal file
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{
"_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": {}
}