2025-01-15 21:09:00 -03:00
|
|
|
from load_dataset import load_data, analisis_univariado
|
2024-12-06 19:08:51 -03:00
|
|
|
from trainer import BinaryTuner
|
|
|
|
|
import pandas as pd
|
|
|
|
|
import numpy as np
|
|
|
|
|
import warnings
|
|
|
|
|
warnings.filterwarnings("ignore")
|
|
|
|
|
|
|
|
|
|
_, dms2, dms3, _ = load_data()
|
|
|
|
|
|
|
|
|
|
|
2025-01-16 13:46:21 -03:00
|
|
|
resultados = analisis_univariado(dms2, target="MODY2_label", continuas=['edad diag', 'IMC', 'glu ayu', 'glu 120','A1c'], discretas=['sexo', 'diabetes_familia'])
|
2025-01-15 21:09:00 -03:00
|
|
|
print(resultados)
|
2024-12-06 19:08:51 -03:00
|
|
|
|
2025-01-15 21:09:00 -03:00
|
|
|
|
|
|
|
|
# mody2 = BinaryTuner(dms2, 'MODY2_label', seeds=[231964], test_size=0.2)
|
|
|
|
|
# mody2.fit()
|
|
|
|
|
# mody2.explain_model('GaussianNB', 'fulldataset-oversampled-mice', 231964)
|
|
|
|
|
# mody2.wrap_and_save()
|
|
|
|
|
#
|
|
|
|
|
#
|
|
|
|
|
# mody3 = BinaryTuner(dms3, 'MODY3_label', seeds=[536202], test_size=0.2)
|
|
|
|
|
# mody3.fit()
|
|
|
|
|
# mody3.explain_model('RandomForestClassifier', 'fulldataset-original-mice', 536202)
|
|
|
|
|
# mody3.wrap_and_save()
|
