Excluded the missing value replacement value from the list of valid v…

…alues
jpmml · Jan 5, 2024 · 4941ef9 · 4941ef9
1 parent b5a362b
commit 4941ef9
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Showing 2 changed files with 4 additions and 10 deletions.
diff --git a/sklearn2pmml/decoration/__init__.py b/sklearn2pmml/decoration/__init__.py
@@ -218,10 +218,6 @@ def fit(self, X, y = None):
 						data_values = self.dtype_.categories
 					else:
 						data_values = numpy.unique(X[nonmissing_mask])
-					if (self.missing_value_replacement is not None) and numpy.any(missing_mask) > 0:
-						if _is_pandas_categorical(self.dtype_):
-							raise ValueError()
-						data_values = numpy.unique(numpy.append(data_values, self.missing_value_replacement))
 				else:
 					data_values = numpy.asarray(self.data_values)
 				self.data_values_ = data_values
@@ -236,8 +232,6 @@ def fit(self, X, y = None):
 						col_missing_mask = missing_mask[:, col]
 						col_nonmissing_mask = nonmissing_mask[:, col]
 						data_values = numpy.unique(col_X[col_nonmissing_mask])
-						if (self.missing_value_replacement is not None) and numpy.any(col_missing_mask) > 0:
-							data_values = numpy.unique(numpy.append(data_values, self.missing_value_replacement))
 					else:
 						data_values = numpy.asarray(self.data_values[col])
 					self.data_values_.append(data_values)

diff --git a/sklearn2pmml/decoration/tests/__init__.py b/sklearn2pmml/decoration/tests/__init__.py
@@ -107,8 +107,8 @@ def test_fit_int_missing(self):
 		Xt = domain.fit_transform(X)
 		self.assertIsInstance(Xt, DataFrame)
 		self.assertEqual(2, len(domain.data_values_))
-		self.assertEqual([0, 1, 2, 3], domain.data_values_[0].tolist())
-		self.assertEqual([0, 1, 2], domain.data_values_[1].tolist())
+		self.assertEqual([1, 2, 3], domain.data_values_[0].tolist())
+		self.assertEqual([1, 2], domain.data_values_[1].tolist())
 		self.assertEqual(2, len(domain.counts_))
 		self.assertEqual({"totalFreq" : 6, "missingFreq" : 2, "invalidFreq" : 0}, domain.counts_[0])
 		self.assertEqual({"totalFreq" : 6, "missingFreq" : 3, "invalidFreq" : 0}, domain.counts_[1])
@@ -182,8 +182,8 @@ def test_fit_string_missing(self):
 		Xt = domain.fit_transform(X)
 		self.assertIsInstance(Xt, DataFrame)
 		self.assertEqual(2, len(domain.data_values_))
-		self.assertEqual(["0", "1", "2", "3"], domain.data_values_[0].tolist())
-		self.assertEqual(["0", "one", "three", "two"], domain.data_values_[1].tolist())
+		self.assertEqual(["1", "2", "3"], domain.data_values_[0].tolist())
+		self.assertEqual(["one", "three", "two"], domain.data_values_[1].tolist())
 		self.assertEqual(2, len(domain.counts_))
 		self.assertEqual({"totalFreq" : 6, "missingFreq" : 2, "invalidFreq" : 0}, domain.counts_[0])
 		self.assertEqual({"totalFreq" : 6, "missingFreq" : 3, "invalidFreq" : 0}, domain.counts_[1])