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BlackboxClassifier based on predictions to work with DatasetWithPredictions

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abigailt 2022-07-24 21:05:12 +03:00 • committed by abigailgold
parent 77a6e08c8e
commit fb534f7a0f
3 changed files with 63 additions and 6 deletions
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33
tests/test_model.py
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@ -3,7 +3,7 @@ import numpy as np
from apt.utils.models import SklearnClassifier, SklearnRegressor, ModelOutputType, KerasClassifier, KerasRegressor, \
BlackboxClassifierPredictions, BlackboxClassifierPredictFunction, is_one_hot, get_nb_classes
from apt.utils.datasets import ArrayDataset, Data
from apt.utils.datasets import ArrayDataset, Data, DatasetWithPredictions
from apt.utils import dataset_utils
from sklearn.tree import DecisionTreeRegressor
@ -104,6 +104,37 @@ def test_blackbox_classifier():
assert model.model_type is None
def test_blackbox_classifier_predictions():
(x_train, y_train), (x_test, y_test) = dataset_utils.get_iris_dataset_np()
train = DatasetWithPredictions(y_train, x_train)
test = DatasetWithPredictions(y_test, x_test)
data = Data(train, test)
model = BlackboxClassifierPredictions(data, ModelOutputType.CLASSIFIER_SCALAR)
pred = model.predict(test)
assert(pred.shape[0] == x_test.shape[0])
assert model.model_type is None
with pytest.raises(ValueError):
model.score(test)
def test_blackbox_classifier_predictions_y():
(x_train, y_train), (x_test, y_test) = dataset_utils.get_iris_dataset_np()
train = DatasetWithPredictions(y_train, x_train, y_train)
test = DatasetWithPredictions(y_test, x_test, y_test)
data = Data(train, test)
model = BlackboxClassifierPredictions(data, ModelOutputType.CLASSIFIER_SCALAR)
pred = model.predict(test)
assert(pred.shape[0] == x_test.shape[0])
score = model.score(test)
assert(score == 1.0)
assert model.model_type is None
def test_blackbox_classifier_mismatch():
(x_train, y_train), (x_test, y_test) = dataset_utils.get_iris_dataset_np()