def test_transfer_transformer_cloned0(self):
X = numpy.array([[0.1], [0.2], [0.3], [0.4], [0.5]])
norm = StandardScaler()
norm.fit(X)
tr1 = TransferTransformer(norm, copy_estimator=True)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=False)
tr1.fit(X)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=False)
tr1 = TransferTransformer(norm, copy_estimator=True)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=True)
tr1.fit(X)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=True)
def test_predictable_tsne_clone(self):
self.maxDiff = None
test_sklearn_clone(lambda: PredictableTSNE())
def test_piecewise_regressor_clone(self):
test_sklearn_clone(lambda: PiecewiseRegressor(verbose=True))
def test_quantile_regression_clone(self):
test_sklearn_clone(lambda: QuantileLinearRegression(delta=0.001))
def test_classifier_clone(self):
test_sklearn_clone(
lambda: DecisionTreeLogisticRegression(fit_improve_algo=None))
def test_classification_kmeans_clone(self):
self.maxDiff = None
test_sklearn_clone(lambda: ClassifierAfterKMeans())
def test_piecewise_classifier_clone(self):
test_sklearn_clone(lambda: PiecewiseClassifier(verbose=True))
def test_categories_to_integers_clone(self):
self.maxDiff = None
test_sklearn_clone(lambda: CategoriesToIntegers())
def test_transfer_transformer_clone(self):
X = numpy.array([[0.1], [0.2], [0.3], [0.4], [0.5]])
Y = numpy.array([1., 1.1, 1.2, 10, 1.4])
norm = StandardScaler()
norm.fit(X)
X2 = norm.transform(X)
clr = LinearRegression()
clr.fit(X2, Y)
tr1 = TransferTransformer(norm, copy_estimator=False)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=True)
tr1.fit(X)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=True)
tr1 = TransferTransformer(norm, copy_estimator=True)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=True)
tr1.fit(X)
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=True)
tr1 = TransferTransformer(norm, copy_estimator=True)
tr2 = TransferTransformer(clr, copy_estimator=True)
pipe = make_pipeline(tr1, tr2)
pipe.fit(X)
self.maxDiff = None
test_sklearn_clone(lambda: tr1, ext=self, copy_fitted=True)
test_sklearn_clone(lambda: tr2, ext=self, copy_fitted=True)
test_sklearn_clone(lambda: pipe, ext=self, copy_fitted=True)
def test_quantile_regression_clone(self):
test_sklearn_clone(lambda: QuantileMLPRegressor())
