-
-
-
-[![mkdocs-shield]][mkdocs-url]
-
-
-## Organisation du projet
-
-```
-├── LICENSE <- Open-source license if one is chosen
-├── Makefile <- Makefile with convenience commands like `make data` or `make train`
-├── README.md <- The top-level README for developers using this project.
-├── data
-│ ├── external <- Data from third party sources.
-│ ├── interim <- Intermediate data that has been transformed.
-│ ├── processed <- The final, canonical data sets for modeling.
-│ └── raw <- The original, immutable data dump.
-│
-├── docs <- A default mkdocs project; see www.mkdocs.org for details
-│
-├── models <- Trained and serialized models, model predictions, or model summaries
-│
-├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
-│ the creator's initials, and a short `-` delimited description, e.g.
-│ `1.0-jqp-initial-data-exploration`.
-│
-├── pyproject.toml <- Project configuration file with package metadata for
-│ projet_05 and configuration for tools like black
-│
-├── references <- Data dictionaries, manuals, and all other explanatory materials.
-│
-├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
-│ └── figures <- Generated graphics and figures to be used in reporting
-│
-├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
-│ generated with `pip freeze > requirements.txt`
-│
-├── setup.cfg <- Configuration file for flake8
-│
-└── projet_05 <- Source code for use in this project.
- │
- ├── __init__.py <- Makes projet_05 a Python module
- │
- ├── config.py <- Store useful variables and configuration
- │
- ├── dataset.py <- Scripts to download or generate data
- │
- ├── features.py <- Code to create features for modeling
- │
- ├── modeling
- │ ├── __init__.py
- │ ├── predict.py <- Code to run model inference with trained models
- │ └── train.py <- Code to train models
- │
- └── plots.py <- Code to create visualizations
-```
-
-## Code hérité réutilisé
-
-- `scripts_projet04/brand` : charte graphique OpenClassrooms (classe `Theme`, palettes, YAML). Le module `projet_05/branding.py` en est la porte d'entrée et applique automatiquement le thème.
-- `scripts_projet04/manet_projet04/shap_generator.py` : fonctions `shap_global` / `shap_local` utilisées par `projet_05/modeling/train.py` pour reproduire les visualisations SHAP.
-
-## Base de données PostgreSQL
-
-Depuis la branche `postgresql`, toute la fusion des fichiers bruts repose sur une base PostgreSQL accessible via SQLAlchemy.
-
-1. Installez PostgreSQL (Homebrew, package officiel, etc.).
-2. Créez un rôle et la base attendue :
-
-> Exemple pour MacOS
-
- ```bash
- /opt/homebrew/opt/postgresql@17/bin/createuser -s postgres
- /opt/homebrew/opt/postgresql@17/bin/psql -d postgres -c "ALTER USER postgres WITH PASSWORD 'postgres';"
- /opt/homebrew/opt/postgresql@17/bin/createdb -O postgres projet05
- ```
-
- Adaptez les chemins/versions selon votre environnement.
-3. Renseignez la chaîne de connexion dans `projet_05/settings.yml` :
-
- ```yaml
- database:
- url: postgresql+psycopg://user:password@host:5432/projet05
- schema: public
- ```
-
- Il est également possible de définir `PROJET05_DATABASE_URL` dans l'environnement.
-
-4. Initialisez la base (création des tables + insertion des CSV d'exemple) avec :
-
- ```bash
- python -m scripts.init_db
- ```
-
-5. Assurez-vous que l'utilisateur possède les droits `CREATE/DROP TABLE` dans le schéma ciblé : les tables `sirh`, `evaluation`, `sond` ainsi que `prediction_logs` seront créées ou recréées à chaque ré-exécution.
-
-6. Lancez ensuite `python -m projet_05.dataset` comme auparavant (ou `python main.py` pour exécuter toutes les étapes). La requête SQL utilisée est toujours exportée dans `reports/merge_sql.sql` pour audit.
-
-> Les interactions utilisateur/modèle (qu'elles proviennent du formulaire, du tableau ou d'un upload) sont automatiquement journalisées dans la table `prediction_logs`, ce qui permet de tracer les usages et de constituer un dataset réel pour le monitoring.
-
-## Tests & couverture
-
-Une batterie de tests Pytest valident l’intégrité de la base PostgreSQL, la fusion des données et la journalisation des prédictions.
-
-1. Démarrez PostgreSQL (cf. section précédente) et créez un utilisateur ayant les droits `CREATE/DROP DATABASE`.
-2. Facultatif : définissez `PROJET05_TEST_DATABASE_URL` si vous souhaitez utiliser une URL différente de `postgresql+psycopg://postgres:postgres@localhost:5432/projet05_test`.
-3. Exécutez les tests et générez le rapport de couverture :
-
- ```bash
- pytest
- ```
+
+
+[![project_license][https://img.shields.io/github/license/stephmnt/OCR_projet05.svg?style=for-the-badge]][https://github.com/stephmnt/OCR_Projet05/blob/main/LICENSE]
+![MkDocs][https://img.shields.io/badge/MkDocs-526CFE?logo=materialformkdocs&logoColor=fff][https://stephmnt.github.io/OCR_Projet05/]
+![[Cookie Cutter][https://img.shields.io/badge/CCDS-Project%20template-328F97?logo=cookiecutter]][https://cookiecutter-data-science.drivendata.org/]
- La configuration Pytest produit à la fois un rapport terminal (`--cov-report=term-missing`) et un fichier `coverage.xml` exploitable par vos outils CI/CD.
- Les sorties complètes sont sauvegardées dans `logs/tests_logs/
-
-
-
- project_description
-
- Explore the docs »
-
-
- View Demo
- ·
- Report Bug
- ·
- Request Feature
-
-Déployez un modèle de Machine Learning
+[![mkdocs-shield]][mkdocs-url]
+
## Organisation du projet
@@ -305,10 +307,6 @@ Project Link: [https://github.com/github_username/repo_name](https://github.com/
[stars-url]: https://github.com/stephmnt/OCR_projet05/stargazers
[issues-shield]: https://img.shields.io/github/issues/stephmnt/OCR_projet05.svg?style=for-the-badge
[issues-url]: https://github.com/stephmnt/OCR_projet05/issues
-[license-shield]: https://img.shields.io/github/license/stephmnt/OCR_projet05.svg?style=for-the-badge
-[license-url]: https://github.com/stephmnt/OCR_projet05/blob/master/LICENSE.txt
-[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555
-[linkedin-url]: https://linkedin.com/in/stephanemanet
[product-screenshot]: images/screenshot.png
[Noobie]: https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16
@@ -328,9 +326,15 @@ Project Link: [https://github.com/github_username/repo_name](https://github.com/
[Bootstrap-url]: https://getbootstrap.com
[JQuery.com]: https://img.shields.io/badge/jQuery-0769AD?style=for-the-badge&logo=jquery&logoColor=white
[JQuery-url]: https://jquery.com
+
+[license-shield]: https://img.shields.io/github/license/stephmnt/OCR_projet05.svg?style=for-the-badge
+[license-url]: https://github.com/stephmnt/OCR_Projet05/blob/main/LICENSE
+[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555
+[linkedin-url]: https://linkedin.com/in/stephanemanet
-[Postgres]: https://img.shields.io/badge/Postgres-%23316192.svg?logo=postgresql&logoColor=white
-[Python]: https://img.shields.io/badge/Python-3776AB?logo=python&logoColor=fff)
-[MkDocs]: https://img.shields.io/badge/MkDocs-526CFE?logo=materialformkdocs&logoColor=fff
+[postgres-shield]: https://img.shields.io/badge/Postgres-%23316192.svg?logo=postgresql&logoColor=white
+[python-shield]: https://img.shields.io/badge/Python-3776AB?logo=python&logoColor=fff)
+[mkdocs-shield]: https://img.shields.io/badge/MkDocs-526CFE?logo=materialformkdocs&logoColor=fff
+[mkdocs-url]: https://stephmnt.github.io/OCR_Projet05/
[NumPy]: https://img.shields.io/badge/NumPy-4DABCF?logo=numpy&logoColor=fff
[](#)
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py
index 1f965c1e74ed05288f01124620de24114bd90735..7be28db810538cb7c0ba84a12b736c162150b158 100644
--- a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py
@@ -17,12 +17,30 @@ SCHEMA_PATH = Path("data/processed/schema.json")
def _load_schema(path: Path) -> dict[str, Any]:
+ """Load the schema definition stored as JSON.
+
+ Args:
+ path: Path to the schema.json file.
+
+ Returns:
+ A dictionary describing the schema or an empty dict if the file is missing.
+ """
if not path.exists():
return {}
return json.loads(path.read_text(encoding="utf-8"))
def _infer_features(metadata: dict, schema: dict, pipeline) -> list[str]:
+ """Infer the ordered list of features expected by the model.
+
+ Args:
+ metadata: Metadata produced during training.
+ schema: Schema derived from `features.py`.
+ pipeline: Loaded sklearn pipeline (optional).
+
+ Returns:
+ List of feature names in the order expected by the model.
+ """
if schema:
candidates = schema.get("numerical_features", []) + schema.get("categorical_features", [])
if candidates:
@@ -37,6 +55,18 @@ def _infer_features(metadata: dict, schema: dict, pipeline) -> list[str]:
def _convert_input(payload: Any, headers: list[str]) -> pd.DataFrame:
+ """Normalize any user input into a validated DataFrame.
+
+ Args:
+ payload: Raw table coming from Gradio (DataFrame, list, etc.).
+ headers: Expected column names.
+
+ Returns:
+ A sanitized DataFrame.
+
+ Raises:
+ gr.Error: If no valid row is provided.
+ """
if isinstance(payload, pd.DataFrame):
df = payload.copy()
elif payload is None:
@@ -50,6 +80,7 @@ def _convert_input(payload: Any, headers: list[str]) -> pd.DataFrame:
def _ensure_model():
+ """Ensure that a pipeline has been loaded before inference."""
if PIPELINE is None:
raise gr.Error(
"Aucun modèle entrainé n'a été trouvé. Lancez `python projet_05/modeling/train.py` puis relancez l'application."
@@ -57,6 +88,7 @@ def _ensure_model():
def score_table(table):
+ """Score data entered via the interactive table."""
_ensure_model()
df = _convert_input(table, FEATURE_ORDER)
drop_cols = [TARGET_COLUMN] if TARGET_COLUMN else None
@@ -70,6 +102,7 @@ def score_table(table):
def score_csv(upload):
+ """Score a CSV uploaded by the user."""
_ensure_model()
if upload is None:
raise gr.Error("Veuillez déposer un fichier CSV.")
@@ -85,6 +118,7 @@ def score_csv(upload):
def predict_from_form(*values):
+ """Score a single row coming from the form tab."""
_ensure_model()
if not FEATURE_ORDER:
raise gr.Error("Impossible de générer le formulaire sans configuration des features.")
@@ -132,7 +166,7 @@ with gr.Blocks(title="Prédicteur d'attrition") as demo:
if PIPELINE is None:
gr.Markdown(
- "⚠️ **Aucun modèle disponible.** Lancez les scripts `dataset.py`, `features.py` puis `modeling/train.py`."
+ "**Aucun modèle disponible.** Lancez les scripts `dataset.py`, `features.py` puis `modeling/train.py`."
)
else:
gr.Markdown(f"Seuil de décision actuel : **{THRESHOLD:.2f}**")
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore
index ba9392bfe7b4a1cea588ba9338eeccbbda3e2436..f733db938eee20501c37e3cd8110476fc9b245ec 100644
--- a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore
@@ -4,6 +4,11 @@
# Mac OS-specific storage files
.DS_Store
*.code-workspace
+*.pdf
+/output/
+questions.md
+*.pdf
+
# vim
*.swp
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md
index a41e41fb44a719e259948e2d5807dab7765cbcb6..3516dcbb6094cc1b1281bbec6a12c41a3ed62408 100644
--- a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md
@@ -1,5 +1,3 @@
-# projet_05
-
---
title: OCR_Projet05
emoji: 🔥
@@ -12,6 +10,8 @@ pinned: true
short_description: Projet 05 formation Openclassrooms
---
+# projet_05
+
@@ -76,17 +76,6 @@ Déployez un modèle de Machine Learning
--------
----
-title: Projet 05
-emoji: 👀
-colorFrom: indigo
-colorTo: green
-sdk: gradio
-sdk_version: 5.49.1
-app_file: app.py
-pinned: false
----
-
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
@@ -99,8 +88,6 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
*** Thanks again! Now go create something AMAZING! :D
-->
-
-
@@ -57,6 +69,11 @@ Déployez un modèle de Machine Learning
└── plots.py <- Code to create visualizations
```
+## Code hérité réutilisé
+
+- `scripts_projet04/brand` : charte graphique OpenClassrooms (classe `Theme`, palettes, YAML). Le module `projet_05/branding.py` en est la porte d'entrée et applique automatiquement le thème.
+- `scripts_projet04/manet_projet04/shap_generator.py` : fonctions `shap_global` / `shap_local` utilisées par `projet_05/modeling/train.py` pour reproduire les visualisations SHAP.
+
--------
---
@@ -93,6 +110,7 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
*** https://www.markdownguide.org/basic-syntax/#reference-style-links
-->
[![Contributors][contributors-shield]][contributors-url]
+[![Python][python]][python]
[![Forks][forks-shield]][forks-url]
[![Stargazers][stars-shield]][stars-url]
[![Issues][issues-shield]][issues-url]
@@ -236,7 +254,7 @@ _For more examples, please refer to the [Documentation](https://example.com)_
- [ ] Feature 3
- [ ] Nested Feature
-See the [open issues](https://github.com/github_username/repo_name/issues) for a full list of proposed features (and known issues).
+See the [open issues](https://github.com/stephmnt/OCR_projet05/issues) for a full list of proposed features (and known issues).
@@ -299,18 +317,18 @@ Project Link: [https://github.com/github_username/repo_name](https://github.com/
-[contributors-shield]: https://img.shields.io/github/contributors/github_username/repo_name.svg?style=for-the-badge
-[contributors-url]: https://github.com/github_username/repo_name/graphs/contributors
-[forks-shield]: https://img.shields.io/github/forks/github_username/repo_name.svg?style=for-the-badge
-[forks-url]: https://github.com/github_username/repo_name/network/members
-[stars-shield]: https://img.shields.io/github/stars/github_username/repo_name.svg?style=for-the-badge
-[stars-url]: https://github.com/github_username/repo_name/stargazers
-[issues-shield]: https://img.shields.io/github/issues/github_username/repo_name.svg?style=for-the-badge
-[issues-url]: https://github.com/github_username/repo_name/issues
-[license-shield]: https://img.shields.io/github/license/github_username/repo_name.svg?style=for-the-badge
-[license-url]: https://github.com/github_username/repo_name/blob/master/LICENSE.txt
+[contributors-shield]: https://img.shields.io/github/contributors/stephmnt/OCR_projet05.svg?style=for-the-badge
+[contributors-url]: https://github.com/stephmnt/OCR_projet05/graphs/contributors
+[forks-shield]: https://img.shields.io/github/forks/stephmnt/OCR_projet05.svg?style=for-the-badge
+[forks-url]: https://github.com/stephmnt/OCR_projet05/network/members
+[stars-shield]: https://img.shields.io/github/stars/stephmnt/OCR_projet05.svg?style=for-the-badge
+[stars-url]: https://github.com/stephmnt/OCR_projet05/stargazers
+[issues-shield]: https://img.shields.io/github/issues/stephmnt/OCR_projet05.svg?style=for-the-badge
+[issues-url]: https://github.com/stephmnt/OCR_projet05/issues
+[license-shield]: https://img.shields.io/github/license/stephmnt/OCR_projet05.svg?style=for-the-badge
+[license-url]: https://github.com/stephmnt/OCR_projet05/blob/master/LICENSE.txt
[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555
-[linkedin-url]: https://linkedin.com/in/linkedin_username
+[linkedin-url]: https://linkedin.com/in/stephanemanet
[product-screenshot]: images/screenshot.png
[Noobie]: https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16
@@ -331,10 +349,8 @@ Project Link: [https://github.com/github_username/repo_name](https://github.com/
[JQuery.com]: https://img.shields.io/badge/jQuery-0769AD?style=for-the-badge&logo=jquery&logoColor=white
[JQuery-url]: https://jquery.com
-[](#)
-[](#)
-[](#)
-[](#)
-[](#)
+[Postgres]: https://img.shields.io/badge/Postgres-%23316192.svg?logo=postgresql&logoColor=white
+[Python]: https://img.shields.io/badge/Python-3776AB?logo=python&logoColor=fff)
+[MkDocs]: https://img.shields.io/badge/MkDocs-526CFE?logo=materialformkdocs&logoColor=fff
+[NumPy]: https://img.shields.io/badge/NumPy-4DABCF?logo=numpy&logoColor=fff
[](#)
-[](#)[text](../projet_04/.gitignore)
\ No newline at end of file
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/LICENSE b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..8a4e372e79bcbdac30db95d6854a88989dec41a3
--- /dev/null
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/LICENSE
@@ -0,0 +1,10 @@
+
+The MIT License (MIT)
+Copyright (c) 2025, Stéphane Manet
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/Makefile b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..2b427a0876c51dc22c314ab9aba95982e4b36ece
--- /dev/null
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/Makefile
@@ -0,0 +1,85 @@
+#################################################################################
+# GLOBALS #
+#################################################################################
+
+PROJECT_NAME = OCR_projet05
+PYTHON_VERSION = 3.10
+PYTHON_INTERPRETER = python
+
+#################################################################################
+# COMMANDS #
+#################################################################################
+
+
+## Install Python dependencies
+.PHONY: requirements
+requirements:
+ pip install -e .
+
+
+
+
+## Delete all compiled Python files
+.PHONY: clean
+clean:
+ find . -type f -name "*.py[co]" -delete
+ find . -type d -name "__pycache__" -delete
+
+
+## Lint using ruff (use `make format` to do formatting)
+.PHONY: lint
+lint:
+ ruff format --check
+ ruff check
+
+## Format source code with ruff
+.PHONY: format
+format:
+ ruff check --fix
+ ruff format
+
+
+
+## Run tests
+.PHONY: test
+test:
+ python -m pytest tests
+
+
+## Set up Python interpreter environment
+.PHONY: create_environment
+create_environment:
+ @bash -c "if [ ! -z `which virtualenvwrapper.sh` ]; then source `which virtualenvwrapper.sh`; mkvirtualenv $(PROJECT_NAME) --python=$(PYTHON_INTERPRETER); else mkvirtualenv.bat $(PROJECT_NAME) --python=$(PYTHON_INTERPRETER); fi"
+ @echo ">>> New virtualenv created. Activate with:\nworkon $(PROJECT_NAME)"
+
+
+
+
+#################################################################################
+# PROJECT RULES #
+#################################################################################
+
+
+## Make dataset
+.PHONY: data
+data: requirements
+ $(PYTHON_INTERPRETER) projet_05/dataset.py
+
+
+#################################################################################
+# Self Documenting Commands #
+#################################################################################
+
+.DEFAULT_GOAL := help
+
+define PRINT_HELP_PYSCRIPT
+import re, sys; \
+lines = '\n'.join([line for line in sys.stdin]); \
+matches = re.findall(r'\n## (.*)\n[\s\S]+?\n([a-zA-Z_-]+):', lines); \
+print('Available rules:\n'); \
+print('\n'.join(['{:25}{}'.format(*reversed(match)) for match in matches]))
+endef
+export PRINT_HELP_PYSCRIPT
+
+help:
+ @$(PYTHON_INTERPRETER) -c "${PRINT_HELP_PYSCRIPT}" < $(MAKEFILE_LIST)
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py
index 04cc31aa8d0e06aeaac3b59bb361ed71d831e43f..1f965c1e74ed05288f01124620de24114bd90735 100644
--- a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/app.py
@@ -1,7 +1,181 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from typing import Any
+
import gradio as gr
+import pandas as pd
+from loguru import logger
+
+from projet_05.branding import apply_brand_theme
+from projet_05.modeling.predict import load_metadata, load_pipeline, run_inference
+
+MODEL_PATH = Path("models/best_model.joblib")
+METADATA_PATH = Path("models/best_model_meta.json")
+SCHEMA_PATH = Path("data/processed/schema.json")
+
+
+def _load_schema(path: Path) -> dict[str, Any]:
+ if not path.exists():
+ return {}
+ return json.loads(path.read_text(encoding="utf-8"))
+
+
+def _infer_features(metadata: dict, schema: dict, pipeline) -> list[str]:
+ if schema:
+ candidates = schema.get("numerical_features", []) + schema.get("categorical_features", [])
+ if candidates:
+ return candidates
+ features = metadata.get("features", {})
+ explicit = (features.get("numerical") or []) + (features.get("categorical") or [])
+ if explicit:
+ return explicit
+ if pipeline is not None and hasattr(pipeline, "feature_names_in_"):
+ return list(pipeline.feature_names_in_)
+ return []
+
+
+def _convert_input(payload: Any, headers: list[str]) -> pd.DataFrame:
+ if isinstance(payload, pd.DataFrame):
+ df = payload.copy()
+ elif payload is None:
+ df = pd.DataFrame(columns=headers)
+ else:
+ df = pd.DataFrame(payload, columns=headers if headers else None)
+ df = df.dropna(how="all")
+ if df.empty:
+ raise gr.Error("Merci de saisir au moins une ligne complète.")
+ return df
+
+
+def _ensure_model():
+ if PIPELINE is None:
+ raise gr.Error(
+ "Aucun modèle entrainé n'a été trouvé. Lancez `python projet_05/modeling/train.py` puis relancez l'application."
+ )
+
+
+def score_table(table):
+ _ensure_model()
+ df = _convert_input(table, FEATURE_ORDER)
+ drop_cols = [TARGET_COLUMN] if TARGET_COLUMN else None
+ return run_inference(
+ df,
+ PIPELINE,
+ THRESHOLD,
+ drop_columns=drop_cols,
+ required_features=FEATURE_ORDER or None,
+ )
+
+
+def score_csv(upload):
+ _ensure_model()
+ if upload is None:
+ raise gr.Error("Veuillez déposer un fichier CSV.")
+ df = pd.read_csv(upload.name)
+ drop_cols = [TARGET_COLUMN] if TARGET_COLUMN else None
+ return run_inference(
+ df,
+ PIPELINE,
+ THRESHOLD,
+ drop_columns=drop_cols,
+ required_features=FEATURE_ORDER or None,
+ )
+
+
+def predict_from_form(*values):
+ _ensure_model()
+ if not FEATURE_ORDER:
+ raise gr.Error("Impossible de générer le formulaire sans configuration des features.")
+ payload = {feature: value for feature, value in zip(FEATURE_ORDER, values)}
+ df = pd.DataFrame([payload])
+ scored = run_inference(
+ df,
+ PIPELINE,
+ THRESHOLD,
+ required_features=FEATURE_ORDER or None,
+ )
+ row = scored.iloc[0]
+ label = "Risque de départ" if int(row["prediction"]) == 1 else "Reste probable"
+ return {
+ "probability": round(float(row["proba_depart"]), 4),
+ "decision": label,
+ "threshold": THRESHOLD,
+ }
+
+
+# Chargement des artéfacts
+apply_brand_theme()
+
+PIPELINE = None
+METADATA: dict[str, Any] = {}
+THRESHOLD = 0.5
+TARGET_COLUMN: str | None = None
+SCHEMA = _load_schema(SCHEMA_PATH)
+
+try:
+ PIPELINE = load_pipeline(MODEL_PATH)
+ METADATA = load_metadata(METADATA_PATH)
+ THRESHOLD = float(METADATA.get("best_threshold", THRESHOLD))
+ TARGET_COLUMN = METADATA.get("target")
+except FileNotFoundError as exc:
+ logger.warning("Artéfact manquant: {}", exc)
+
+FEATURE_ORDER = _infer_features(METADATA, SCHEMA, PIPELINE)
+
+with gr.Blocks(title="Prédicteur d'attrition") as demo:
+ gr.Markdown("# API Gradio – Prédiction de départ employé")
+ gr.Markdown(
+ "Le modèle applique le pipeline entraîné hors-notebook pour fournir une probabilité de départ ainsi qu'une décision binaire."
+ )
+
+ if PIPELINE is None:
+ gr.Markdown(
+ "⚠️ **Aucun modèle disponible.** Lancez les scripts `dataset.py`, `features.py` puis `modeling/train.py`."
+ )
+ else:
+ gr.Markdown(f"Seuil de décision actuel : **{THRESHOLD:.2f}**")
+
+ with gr.Tab("Formulaire unitaire"):
+ if not FEATURE_ORDER:
+ gr.Markdown("Aucune configuration de features détectée. Utilisez l'onglet CSV pour scorer vos données.")
+ else:
+ form_inputs: list[gr.components.Component] = [] # type: ignore
+ for feature in FEATURE_ORDER:
+ form_inputs.append(
+ gr.Textbox(label=feature, placeholder=f"Saisir {feature.replace('_', ' ')}")
+ )
+ form_output = gr.JSON(label="Résultat")
+ gr.Button("Prédire").click(
+ fn=predict_from_form,
+ inputs=form_inputs,
+ outputs=form_output,
+ )
+
+ with gr.Tab("Tableau interactif"):
+ table_input = gr.Dataframe(
+ headers=FEATURE_ORDER if FEATURE_ORDER else None,
+ row_count=(1, "dynamic"),
+ col_count=(len(FEATURE_ORDER), "dynamic") if FEATURE_ORDER else (5, "dynamic"),
+ type="pandas",
+ )
+ table_output = gr.Dataframe(label="Prédictions", type="pandas")
+ gr.Button("Scorer les lignes").click(
+ fn=score_table,
+ inputs=table_input,
+ outputs=table_output,
+ )
+
+ with gr.Tab("Fichier CSV"):
+ file_input = gr.File(file_types=[".csv"], label="Déposez votre fichier CSV")
+ file_output = gr.Dataframe(label="Résultats CSV", type="pandas")
+ gr.Button("Scorer le fichier").click(
+ fn=score_csv,
+ inputs=file_input,
+ outputs=file_output,
+ )
-def greet(name):
- return "Hello " + name + "!!"
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+if __name__ == "__main__":
+ demo.launch()
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.github/workflows/deploy.yml b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.github/workflows/deploy.yml
index 66630672a37802677bb5a36cea6d29af4b2eb758..dbf1ddaaf3b69f2344f846eb6012ecb1b9b04391 100644
--- a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.github/workflows/deploy.yml
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.github/workflows/deploy.yml
@@ -1,10 +1,13 @@
-name: Déployer vers Hugging Face Spaces
+name: Deploy to Hugging Face Spaces
on:
push:
branches:
- main
+permissions:
+ contents: write
+
jobs:
deploy:
runs-on: ubuntu-latest
@@ -23,7 +26,7 @@ jobs:
python -m pip install --upgrade pip
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
- - name: Push to Hugging Face Space
+ - name: Deploy to Hugging Face Space
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
@@ -33,5 +36,5 @@ jobs:
rsync -av --exclude '.git' ./ hf_space/
cd hf_space
git add .
- git commit -m "🚀 Auto-deploy from GitHub Actions"
- git push https://stephmnt:$HF_TOKEN@huggingface.co/spaces/stephmnt/projet_05 main
+ git commit -m "🚀 Auto-deploy from GitHub Actions" || echo "No changes to commit"
+ git push https://stephmnt:$HF_TOKEN@huggingface.co/spaces/stephmnt/projet_05 main
\ No newline at end of file
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore
index 85bf600ea236ca40a825047c887d25624c358668..ba9392bfe7b4a1cea588ba9338eeccbbda3e2436 100644
--- a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/.gitignore
@@ -1,2 +1,192 @@
+# Data
+/data/
+
+# Mac OS-specific storage files
+.DS_Store
*.code-workspace
-.venv/
+
+# vim
+*.swp
+*.swo
+
+## https://github.com/github/gitignore/blob/e8554d85bf62e38d6db966a50d2064ac025fd82a/Python.gitignore
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# MkDocs documentation
+docs/site/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+# For a library or package, you might want to ignore these files since the code is
+# intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# UV
+# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+# This is especially recommended for binary packages to ensure reproducibility, and is more
+# commonly ignored for libraries.
+#uv.lock
+
+# poetry
+# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+# This is especially recommended for binary packages to ensure reproducibility, and is more
+# commonly ignored for libraries.
+# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+# in version control.
+# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# pixi
+# pixi.lock should be committed to version control for reproducibility
+# .pixi/ contains the environments and should not be committed
+.pixi/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+# and can be added to the global gitignore or merged into this file. For a more nuclear
+# option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
\ No newline at end of file
diff --git a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md
index 568b6d98de3a2772b983b235c8e74cc11fd83c2a..9e80ceb32bd971250093bf39043d814a10c538ff 100644
--- a/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md
+++ b/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/hf_space/README.md
@@ -1,3 +1,64 @@
+# projet_05
+
+
+
+
+
+Déployez un modèle de Machine Learning
+
+## Organisation du projet
+
+```
+├── LICENSE <- Open-source license if one is chosen
+├── Makefile <- Makefile with convenience commands like `make data` or `make train`
+├── README.md <- The top-level README for developers using this project.
+├── data
+│ ├── external <- Data from third party sources.
+│ ├── interim <- Intermediate data that has been transformed.
+│ ├── processed <- The final, canonical data sets for modeling.
+│ └── raw <- The original, immutable data dump.
+│
+├── docs <- A default mkdocs project; see www.mkdocs.org for details
+│
+├── models <- Trained and serialized models, model predictions, or model summaries
+│
+├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
+│ the creator's initials, and a short `-` delimited description, e.g.
+│ `1.0-jqp-initial-data-exploration`.
+│
+├── pyproject.toml <- Project configuration file with package metadata for
+│ projet_05 and configuration for tools like black
+│
+├── references <- Data dictionaries, manuals, and all other explanatory materials.
+│
+├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
+│ └── figures <- Generated graphics and figures to be used in reporting
+│
+├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
+│ generated with `pip freeze > requirements.txt`
+│
+├── setup.cfg <- Configuration file for flake8
+│
+└── projet_05 <- Source code for use in this project.
+ │
+ ├── __init__.py <- Makes projet_05 a Python module
+ │
+ ├── config.py <- Store useful variables and configuration
+ │
+ ├── dataset.py <- Scripts to download or generate data
+ │
+ ├── features.py <- Code to create features for modeling
+ │
+ ├── modeling
+ │ ├── __init__.py
+ │ ├── predict.py <- Code to run model inference with trained models
+ │ └── train.py <- Code to train models
+ │
+ └── plots.py <- Code to create visualizations
+```
+
+--------
+
---
title: Projet 05
emoji: 👀
@@ -10,3 +71,270 @@ pinned: false
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+
+
+
+
+
+
+
+
+[![Contributors][contributors-shield]][contributors-url]
+[![Forks][forks-shield]][forks-url]
+[![Stargazers][stars-shield]][stars-url]
+[![Issues][issues-shield]][issues-url]
+[![project_license][license-shield]][license-url]
+[![LinkedIn][linkedin-shield]][linkedin-url]
+
+
+
+
+
+
+
+
+
+ project_description
+
+ Explore the docs »
+
+
+ View Demo
+ ·
+ Report Bug
+ ·
+ Request Feature
+
| \n", + " | name | \n", + "
|---|---|
| 0 | \n", + "id_employee | \n", + "
| 1 | \n", + "age | \n", + "
| 2 | \n", + "genre | \n", + "
| 3 | \n", + "revenu_mensuel | \n", + "
| 4 | \n", + "statut_marital | \n", + "
| 5 | \n", + "departement | \n", + "
| 6 | \n", + "poste | \n", + "
| 7 | \n", + "nombre_experiences_precedentes | \n", + "
| 8 | \n", + "nombre_heures_travailless | \n", + "
| 9 | \n", + "annee_experience_totale | \n", + "
| 10 | \n", + "annees_dans_l_entreprise | \n", + "
| 11 | \n", + "annees_dans_le_poste_actuel | \n", + "
| 12 | \n", + "satisfaction_employee_environnement | \n", + "
| 13 | \n", + "note_evaluation_precedente | \n", + "
| 14 | \n", + "niveau_hierarchique_poste | \n", + "
| 15 | \n", + "satisfaction_employee_nature_travail | \n", + "
| 16 | \n", + "satisfaction_employee_equipe | \n", + "
| 17 | \n", + "satisfaction_employee_equilibre_pro_perso | \n", + "
| 18 | \n", + "note_evaluation_actuelle | \n", + "
| 19 | \n", + "heure_supplementaires | \n", + "
| 20 | \n", + "augementation_salaire_precedente | \n", + "
| 21 | \n", + "a_quitte_l_entreprise | \n", + "
| 22 | \n", + "nombre_participation_pee | \n", + "
| 23 | \n", + "nb_formations_suivies | \n", + "
| 24 | \n", + "nombre_employee_sous_responsabilite | \n", + "
| 25 | \n", + "distance_domicile_travail | \n", + "
| 26 | \n", + "niveau_education | \n", + "
| 27 | \n", + "domaine_etude | \n", + "
| 28 | \n", + "ayant_enfants | \n", + "
| 29 | \n", + "frequence_deplacement | \n", + "
| 30 | \n", + "annees_depuis_la_derniere_promotion | \n", + "
| 31 | \n", + "annes_sous_responsable_actuel | \n", + "
| 32 | \n", + "augmentation_par_revenu | \n", + "
| 33 | \n", + "annee_sur_poste_par_experience | \n", + "
| 34 | \n", + "nb_formation_par_experience | \n", + "
| 35 | \n", + "score_moyen_satisfaction | \n", + "
| 36 | \n", + "dern_promo_par_experience | \n", + "
| 37 | \n", + "evolution_note | \n", + "
| \n", + " | model | \n", + "best_params | \n", + "best_threshold | \n", + "F1 | \n", + "Recall | \n", + "Precision | \n", + "ROC_AUC | \n", + "
|---|---|---|---|---|---|---|---|
| 1 | \n", + "RF_balanced | \n", + "{'clf__max_depth': 10, 'clf__min_samples_leaf'... | \n", + "0.490292 | \n", + "0.920934 | \n", + "0.911598 | \n", + "0.930464 | \n", + "0.971614 | \n", + "
| 0 | \n", + "LogReg_balanced | \n", + "{'clf__C': 1.0, 'clf__penalty': 'l1', 'clf__so... | \n", + "0.553559 | \n", + "0.905837 | \n", + "0.862125 | \n", + "0.954219 | \n", + "0.954884 | \n", + "
| \n", + " | model | \n", + "best_params | \n", + "best_threshold | \n", + "F1 | \n", + "Recall | \n", + "Precision | \n", + "ROC_AUC | \n", + "
|---|---|---|---|---|---|---|---|
| 1 | \n", + "RF_balanced | \n", + "{'clf__max_depth': 10, 'clf__min_samples_leaf'... | \n", + "0.490292 | \n", + "0.920934 | \n", + "0.911598 | \n", + "0.930464 | \n", + "0.971614 | \n", + "
| 0 | \n", + "LogReg_balanced | \n", + "{'clf__C': 1.0, 'clf__penalty': 'l1', 'clf__so... | \n", + "0.553559 | \n", + "0.905837 | \n", + "0.862125 | \n", + "0.954219 | \n", + "0.954884 | \n", + "
| \n", - " | name | \n", - "
|---|---|
| 0 | \n", - "id_employee | \n", - "
| 1 | \n", - "age | \n", - "
| 2 | \n", - "genre | \n", - "
| 3 | \n", - "revenu_mensuel | \n", - "
| 4 | \n", - "statut_marital | \n", - "
| 5 | \n", - "departement | \n", - "
| 6 | \n", - "poste | \n", - "
| 7 | \n", - "nombre_experiences_precedentes | \n", - "
| 8 | \n", - "nombre_heures_travailless | \n", - "
| 9 | \n", - "annee_experience_totale | \n", - "
| 10 | \n", - "annees_dans_l_entreprise | \n", - "
| 11 | \n", - "annees_dans_le_poste_actuel | \n", - "
| 12 | \n", - "satisfaction_employee_environnement | \n", - "
| 13 | \n", - "note_evaluation_precedente | \n", - "
| 14 | \n", - "niveau_hierarchique_poste | \n", - "
| 15 | \n", - "satisfaction_employee_nature_travail | \n", - "
| 16 | \n", - "satisfaction_employee_equipe | \n", - "
| 17 | \n", - "satisfaction_employee_equilibre_pro_perso | \n", - "
| 18 | \n", - "note_evaluation_actuelle | \n", - "
| 19 | \n", - "heure_supplementaires | \n", - "
| 20 | \n", - "augementation_salaire_precedente | \n", - "
| 21 | \n", - "a_quitte_l_entreprise | \n", - "
| 22 | \n", - "nombre_participation_pee | \n", - "
| 23 | \n", - "nb_formations_suivies | \n", - "
| 24 | \n", - "nombre_employee_sous_responsabilite | \n", - "
| 25 | \n", - "distance_domicile_travail | \n", - "
| 26 | \n", - "niveau_education | \n", - "
| 27 | \n", - "domaine_etude | \n", - "
| 28 | \n", - "ayant_enfants | \n", - "
| 29 | \n", - "frequence_deplacement | \n", - "
| 30 | \n", - "annees_depuis_la_derniere_promotion | \n", - "
| 31 | \n", - "annes_sous_responsable_actuel | \n", - "
| 32 | \n", - "augmentation_par_revenu | \n", - "
| 33 | \n", - "annee_sur_poste_par_experience | \n", - "
| 34 | \n", - "nb_formation_par_experience | \n", - "
| 35 | \n", - "score_moyen_satisfaction | \n", - "
| 36 | \n", - "dern_promo_par_experience | \n", - "
| 37 | \n", - "evolution_note | \n", - "
| \n", - " | model | \n", - "best_params | \n", - "best_threshold | \n", - "F1 | \n", - "Recall | \n", - "Precision | \n", - "ROC_AUC | \n", - "
|---|---|---|---|---|---|---|---|
| 1 | \n", - "RF_balanced | \n", - "{'clf__max_depth': 10, 'clf__min_samples_leaf'... | \n", - "0.490292 | \n", - "0.920934 | \n", - "0.911598 | \n", - "0.930464 | \n", - "0.971614 | \n", - "
| 0 | \n", - "LogReg_balanced | \n", - "{'clf__C': 1.0, 'clf__penalty': 'l1', 'clf__so... | \n", - "0.553559 | \n", - "0.905837 | \n", - "0.862125 | \n", - "0.954219 | \n", - "0.954884 | \n", - "
| \n", - " | model | \n", - "best_params | \n", - "best_threshold | \n", - "F1 | \n", - "Recall | \n", - "Precision | \n", - "ROC_AUC | \n", - "
|---|---|---|---|---|---|---|---|
| 1 | \n", - "RF_balanced | \n", - "{'clf__max_depth': 10, 'clf__min_samples_leaf'... | \n", - "0.490292 | \n", - "0.920934 | \n", - "0.911598 | \n", - "0.930464 | \n", - "0.971614 | \n", - "
| 0 | \n", - "LogReg_balanced | \n", - "{'clf__C': 1.0, 'clf__penalty': 'l1', 'clf__so... | \n", - "0.553559 | \n", - "0.905837 | \n", - "0.862125 | \n", - "0.954219 | \n", - "0.954884 | \n", - "
+ 
+ 
+