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cleaning basic

This commit is contained in:
Alejandro Moreo Fernandez 2025-07-19 19:38:14 +02:00
parent 265fcc2d92
commit 92f1fd2020
2 changed files with 4 additions and 2 deletions
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3
examples/0.basics.py
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@ -6,6 +6,7 @@ import numpy as np
from sklearn.linear_model import LogisticRegression from sklearn.linear_model import LogisticRegression
import quapy as qp import quapy as qp
from quapy.method.aggregative import PACC
# let's fetch some dataset to run one experiment # let's fetch some dataset to run one experiment
# datasets are available in the "qp.data.datasets" module (there is a shortcut in qp.datasets) # datasets are available in the "qp.data.datasets" module (there is a shortcut in qp.datasets)
@ -34,7 +35,7 @@ print(f'training prevalence = {F.strprev(train.prevalence())}')
# let us train one quantifier, for example, PACC using a sklearn's Logistic Regressor as the underlying classifier # let us train one quantifier, for example, PACC using a sklearn's Logistic Regressor as the underlying classifier
classifier = LogisticRegression() classifier = LogisticRegression()
pacc = qp.method.aggregative.PACC(classifier) pacc = PACC(classifier)
print(f'training {pacc}') print(f'training {pacc}')
pacc.fit(X, y) pacc.fit(X, y)

3
examples/1.model_selection.py
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@ -24,7 +24,8 @@ print(f'running model selection with N_JOBS={qp.environ["N_JOBS"]}; '
training, test = qp.datasets.fetch_UCIMulticlassDataset('letter').train_test training, test = qp.datasets.fetch_UCIMulticlassDataset('letter').train_test
# evaluation in terms of MAE with default hyperparameters # evaluation in terms of MAE with default hyperparameters
model.fit(*training.Xy) Xtr, ytr = training.Xy
model.fit(Xtr, ytr)
mae_score = qp.evaluation.evaluate(model, protocol=UPP(test), error_metric='mae') mae_score = qp.evaluation.evaluate(model, protocol=UPP(test), error_metric='mae')
print(f'MAE (non optimized)={mae_score:.5f}') print(f'MAE (non optimized)={mae_score:.5f}')