Source code for discrimintools.datasets.load_alcools
# -*- coding: utf-8 -*-
from pandas import read_excel
from pathlib import Path
#set directory
DATASETS_DIR = Path(__file__).parent / "data"
[docs]
def load_alcools(element="train"):
"""
Alcools dataset
Parameters
----------
element : str, default = 'train'
The dataset to load. Possible values are:
- 'train' for training dataset.
- 'test' for testing dataset.
Returns
-------
alcools : DataFrame of shape (n_samples, n_columns)
The alcools dataset.
References
----------
[1] Ricco Rakotomalala (2020), « `Pratique de l'Analyse Discriminante Linéaire <https://hal.science/hal-04868585v1/file/Pratique_Analyse_Discriminante_Lineaire.pdf>`_ », Version 1.0, Université Lumière Lyon 2.
Examples
--------
>>> from discrimintools.datasets import load_alcools
>>> from discrimintools import DISCRIM
>>> D = load_alcools("train") # load training data
>>> y, X = D["TYPE"], D.drop(columns=["TYPE"]) # split into X and y
>>> clf = DISCRIM()
>>> clf.fit(X,y)
DISCRIM(priors='prop')
"""
if element == "train":
alcools = read_excel(DATASETS_DIR/"alcools.xlsx",header=0,sheet_name="Feuil1")
elif element == "test":
alcools = read_excel(DATASETS_DIR/"alcools.xlsx",header=0,sheet_name="Feuil2")
else:
raise ValueError("'element' should be one of 'train', 'test'.")
#set cocumentation
alcools.__doc__ = """
Alcools dataset
"""
return alcools