# joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main architecture

> Architecture diagram of the GitHub repository joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-11-10). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main
- Repository: https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main

## Overview

Repositorio de pronóstico jerárquico de demanda intermitente en retail: compara siete benchmarks con un pipeline ES-GBM que pronostica a nivel Familia y desagrega a SKU. El orquestador ejecuta los scripts y consolida resultados. Los excerpts confirman la reutilización de feature engineering y los pasos principales de algunos benchmarks; las conexiones del pipeline final también se apoyan en las descripciones del README. No se inspeccionaron los archivos de entrada, que no aparecen en el árbol.

Main entry points: [`run_all_benchmarks.py`](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/run_all_benchmarks.py) (Orquestador), [`02_modelo_final/2)_esgbm_ensemble.py`](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/2)_esgbm_ensemble.py) (Ensemble familia), [`02_modelo_final/1)_feature_engineering.py`](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/1)_feature_engineering.py) (Features de panel), [`02_modelo_final/3)_desagregacion_sku_share.py`](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/3)_desagregacion_sku_share.py) (Shares SKU)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_benchmarks["Benchmarks"]
  node_sarima["SARIMA"]
  node_sarimax["SARIMAX"]
  node_lstm["LSTM<br/>[c&#41;_lstm_topdown.py]"]
  node_chronos["Chronos-Bolt"]
  node_seasonal["Seasonal Naive"]
  node_croston["Croston"]
  node_sba["SBA<br/>[g&#41;_sba_topdown.py]"]
end

subgraph group_pipeline["Pipeline ES-GBM"]
  node_features["Features de panel"]
  node_ensemble["Ensemble familia"]
  node_shares["Shares SKU"]
end

subgraph group_runtime["Ejecución"]
  node_runner["Orquestador"]
end

subgraph group_artifacts["Resultados"]
  node_workbook["Resultados consolidados"]
end

node_data[("Datos mensuales")]
node_tabpfn{{"TabPFN"}}

node_data -->|"lee datos"| node_sarima
node_data -->|"lee datos"| node_sarimax
node_data -->|"lee datos"| node_lstm
node_data -->|"lee datos"| node_chronos
node_data -->|"lee datos"| node_croston
node_data -->|"lee datos"| node_sba
node_data -->|"prepara panel"| node_features
node_features -->|"provee features"| node_ensemble
node_features -->|"provee features"| node_shares
node_ensemble -->|"pronostica familia"| node_shares
node_tabpfn -.->|"apoya ensamble"| node_ensemble
node_runner -->|"ejecuta"| node_sarima
node_runner -->|"ejecuta"| node_sarimax
node_runner -->|"ejecuta"| node_lstm
node_runner -->|"ejecuta"| node_chronos
node_runner -->|"ejecuta"| node_seasonal
node_runner -->|"ejecuta"| node_croston
node_runner -->|"ejecuta"| node_sba
node_runner -->|"ejecuta"| node_ensemble
node_runner -->|"ejecuta"| node_shares
node_runner -->|"consolida resultados"| node_workbook

click node_sarima "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/a)_sarima_topdown.py"
click node_sarimax "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/b)_sarimax_topdown.py"
click node_lstm "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/c)_lstm_topdown.py"
click node_chronos "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/d)_chronos_topdown.py"
click node_seasonal "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/e)_seasonal_naive_topdown.py"
click node_croston "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/f)_croston_topdown.py"
click node_sba "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/g)_sba_topdown.py"
click node_features "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/1)_feature_engineering.py"
click node_ensemble "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/2)_esgbm_ensemble.py"
click node_shares "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/3)_desagregacion_sku_share.py"
click node_runner "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/run_all_benchmarks.py"
click node_workbook "https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/resultados/RESULTADOS_TESIS_CONSOLIDADO.xlsx"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_sarima,node_sarimax,node_lstm,node_chronos,node_seasonal,node_croston,node_sba toneBlue
class node_features,node_ensemble,node_shares,node_data toneAmber
class node_runner toneMint
class node_workbook toneRose
class node_tabpfn toneIndigo
```

## Components

### Benchmarks

- [SARIMA](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/a)_sarima_topdown.py): `01_modelos_base/a)_sarima_topdown.py`
- [SARIMAX](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/b)_sarimax_topdown.py): `01_modelos_base/b)_sarimax_topdown.py`
- [LSTM](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/c)_lstm_topdown.py): `01_modelos_base/c)_lstm_topdown.py`
- [Chronos-Bolt](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/d)_chronos_topdown.py): `01_modelos_base/d)_chronos_topdown.py`
- [Seasonal Naive](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/e)_seasonal_naive_topdown.py): `01_modelos_base/e)_seasonal_naive_topdown.py`
- [Croston](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/f)_croston_topdown.py): `01_modelos_base/f)_croston_topdown.py`
- [SBA](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/01_modelos_base/g)_sba_topdown.py): `01_modelos_base/g)_sba_topdown.py`

### Pipeline ES-GBM

- [Features de panel](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/1)_feature_engineering.py): `02_modelo_final/1)_feature_engineering.py`
- [Ensemble familia](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/2)_esgbm_ensemble.py): `02_modelo_final/2)_esgbm_ensemble.py`
- [Shares SKU](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/02_modelo_final/3)_desagregacion_sku_share.py): `02_modelo_final/3)_desagregacion_sku_share.py`

### Ejecución

- [Orquestador](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/run_all_benchmarks.py): `run_all_benchmarks.py`

### Resultados

- [Resultados consolidados](https://github.com/joaquinignaciomondaca-code/pronostico-jerarquico-de-demanda-intermitente-en-el-retail-de-moda-femenina-main/blob/main/resultados/RESULTADOS_TESIS_CONSOLIDADO.xlsx): `resultados/RESULTADOS_TESIS_CONSOLIDADO.xlsx`

### Other components

- **Datos mensuales**
- **TabPFN**

## Connections

- Datos mensuales → SARIMA: lee datos (evidence: `01_modelos_base/a)_sarima_topdown.py`)
- Datos mensuales → SARIMAX: lee datos (evidence: `01_modelos_base/b)_sarimax_topdown.py`)
- Datos mensuales → LSTM: lee datos (evidence: `01_modelos_base/c)_lstm_topdown.py`)
- Datos mensuales → Chronos-Bolt: lee datos (evidence: `01_modelos_base/d)_chronos_topdown.py`)
- Datos mensuales → Croston: lee datos (evidence: `01_modelos_base/f)_croston_topdown.py`)
- Datos mensuales → SBA: lee datos (evidence: `01_modelos_base/g)_sba_topdown.py`)
- Datos mensuales → Features de panel: prepara panel (evidence: `README.md`)
- Features de panel → Ensemble familia: provee features (evidence: `02_modelo_final/2)_esgbm_ensemble.py`)
- Features de panel → Shares SKU: provee features (evidence: `02_modelo_final/3)_desagregacion_sku_share.py`)
- Ensemble familia → Shares SKU: pronostica familia (evidence: `README.md`)
- TabPFN → Ensemble familia: apoya ensamble (evidence: `README.md`)
- Orquestador → SARIMA: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → SARIMAX: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → LSTM: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → Chronos-Bolt: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → Seasonal Naive: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → Croston: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → SBA: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → Ensemble familia: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → Shares SKU: ejecuta (evidence: `run_all_benchmarks.py`)
- Orquestador → Resultados consolidados: consolida resultados (evidence: `run_all_benchmarks.py`)