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6
.github/workflows/python-app.yml
vendored
6
.github/workflows/python-app.yml
vendored
@@ -19,15 +19,15 @@ jobs:
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python 3.10
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- name: Set up Python 3.x
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uses: actions/setup-python@v4
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with:
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python-version: "3.10"
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python-version: "3.x"
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- name: install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install ".[test,doc]"
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pip install ".[test]"
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- name: Lint with flake8
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run: |
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5
.github/workflows/static.yml
vendored
5
.github/workflows/static.yml
vendored
@@ -32,15 +32,14 @@ jobs:
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- name: Checkout
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uses: actions/checkout@v4
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- name: Set up Python 3.10
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- name: Set up Python 3.x
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uses: actions/setup-python@v5
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with:
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python-version: '3.10'
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python-version: '3.x'
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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# Installe le projet en mode éditable avec les extras de doc
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pip install -e ".[doc]"
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- name: Setup Pages
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21
LICENSE
Normal file
21
LICENSE
Normal file
@@ -0,0 +1,21 @@
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MIT License
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Copyright (c) 2026 Loïc GUEZO and chahrazad DAHMANI
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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@@ -3,7 +3,7 @@
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> A **University of Paris-Est Créteil (UPEC)** Semester 6 project.
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## Documentation
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- 🇫🇷 [Version Française](https://guezoloic.github.io/millesima-ai-engine)
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- 🇫🇷 [Version Française](https://millesima-ai.github.guezoloic.com)
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> note: only french version enabled for now.
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---
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@@ -12,7 +12,7 @@
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1. **Clone the repository:**
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```bash
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git clone https://github.com/votre-pseudo/millesima-ai-engine.git
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git clone https://github.com/guezoloic/millesima-ai-engine.git
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cd millesima-ai-engine
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```
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@@ -5,12 +5,12 @@ L’objectif de ce projet est d’étudier, en utilisant des méthodes d’appre
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## projet
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<div style="text-align: center;">
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<object
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data="/millesima-ai-engine/projet.pdf"
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data="/projet.pdf"
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type="application/pdf"
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width="100%"
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height="1000px"
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>
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<p>Votre navigateur ne peut pas afficher ce PDF.
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<a href="/millesima-ai-engine/projet.pdf">Cliquez ici pour le télécharger.</a></p>
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<a href="/projet.pdf">Cliquez ici pour le télécharger.</a></p>
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</object>
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</div>
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1287
docs/learning.ipynb
Normal file
1287
docs/learning.ipynb
Normal file
File diff suppressed because one or more lines are too long
@@ -1,5 +1,5 @@
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site_name: "Projet Millesima S6"
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site_url: "https://github.guezoloic.com/millesima-ai-engine/"
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site_url: "https://millesima-ai.github.guezoloic.com"
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theme:
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name: "material"
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@@ -7,6 +7,7 @@ theme:
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plugins:
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- search
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- mkdocstrings
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- mkdocs-jupyter
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extra:
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generator: false
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@@ -1,11 +1,14 @@
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[project]
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name = "projet-millesima-s6"
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name = "millesima-project-s6"
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version = "0.1.0"
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dependencies = [
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"requests==2.32.5",
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"requests==2.33.0",
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"beautifulsoup4==4.14.3",
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"pandas==2.3.3",
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"pandas==3.0.1",
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"tqdm==4.67.3",
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"scikit-learn==1.8.0",
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"matplotlib==3.10.8",
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"seaborn==0.13.2"
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]
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[tool.pytest.ini_options]
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@@ -13,8 +16,13 @@ pythonpath = "src"
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testpaths = ["tests"]
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[project.optional-dependencies]
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test = ["pytest==8.4.2", "requests-mock==1.12.1", "flake8==7.3.0"]
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doc = ["mkdocs<2.0.0", "mkdocs-material==9.6.23", "mkdocstrings[python]"]
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test = ["pytest==9.0.2", "requests-mock==1.12.1", "flake8==7.3.0"]
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doc = [
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"mkdocs<2.0.0",
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"mkdocs-material==9.7.6",
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"mkdocstrings[python]",
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"mkdocs-jupyter==0.26.1",
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]
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[build-system]
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requires = ["setuptools", "wheel"]
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@@ -92,18 +92,25 @@ class Cleaning:
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self._vins = self._vins.join(appellation_dummies)
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return self
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def drop_empty_price(self) -> "Cleaning":
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self._vins = self._vins.dropna(subset=["Prix"])
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return self
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def main() -> None:
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def main(filename: str | None = None) -> None:
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if not filename:
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if len(argv) != 2:
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raise ValueError(f"Usage: {argv[0]} <filename.csv>")
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filename = argv[1]
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cleaning: Cleaning = Cleaning(filename)
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cleaning.drop_empty_appellation() \
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.fill_missing_scores() \
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.encode_appellation() \
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.getVins() \
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.to_csv("clean.csv", index=False)
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cleaning: Cleaning = (
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Cleaning(filename)
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.drop_empty_appellation()
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.fill_missing_scores()
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.encode_appellation()
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.drop_empty_price()
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)
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cleaning.getVins().to_csv("clean.csv", index=False)
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if __name__ == "__main__":
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64
src/learning.py
Executable file
64
src/learning.py
Executable file
@@ -0,0 +1,64 @@
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# from typing import Any, Callable
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# from pandas import DataFrame
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# from sklearn.linear_model import LinearRegression
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# from sklearn.preprocessing import StandardScaler
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# from sklearn.model_selection import train_test_split
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# from sklearn.pipeline import make_pipeline
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# import matplotlib.pyplot as plt
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# from cleaning import Cleaning
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# class Learning:
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# def __init__(self, vins: DataFrame, target: str) -> None:
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# self.X = vins.drop(target, axis=1)
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# self.y = vins[target]
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# self.X_train, self.X_test, self.y_train, self.y_test = train_test_split(
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# self.X, self.y, test_size=0.25, random_state=49
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# )
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# def evaluate(
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# self,
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# estimator,
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# pretreatment=None,
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# fn_score=lambda m, xt, yt: m.score(xt, yt),
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# ):
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# pipeline = make_pipeline(pretreatment, estimator) if pretreatment else estimator
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# pipeline.fit(self.X_train, self.y_train)
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# score = fn_score(pipeline, self.X_test, self.y_test)
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# prediction = pipeline.predict(self.X_test)
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# return score, prediction
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# def draw(self, predictions, y_actual):
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# plt.figure(figsize=(8, 6))
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# plt.scatter(
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# predictions,
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# y_actual,
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# alpha=0.5,
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# c="royalblue",
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# edgecolors="k",
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# label="Vins",
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# )
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# mn = min(predictions.min(), y_actual.min())
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# mx = max(predictions.max(), y_actual.max())
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# plt.plot(
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# [mn, mx],
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# [mn, mx],
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# color="red",
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# linestyle="--",
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# lw=2,
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# label="Prédiction Parfaite",
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# )
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# plt.xlabel("Prix estimés (estim_LR)")
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# plt.ylabel("Prix réels (y_test)")
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# plt.title("titre")
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# plt.legend()
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# plt.grid(True, linestyle=":", alpha=0.6)
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# plt.show()
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@@ -490,9 +490,10 @@ class Scraper:
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savestate((page, cache))
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def main() -> None:
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def main(filename: str | None = None, suburl: str | None = None) -> None:
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if filename is None or suburl is None:
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if len(argv) != 3:
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raise ValueError(f"{argv[0]} <filename> <sous-url>")
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raise ValueError(f"Usage: python {argv[0]} <filename> <sous-url>")
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filename = argv[1]
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suburl = argv[2]
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Reference in New Issue
Block a user