removed PartialFit method from CountVectoriser

vectorisers.go

@@ -166,18 +166,6 @@ func (v *CountVectoriser) Fit(train ...string) Vectoriser {
 	return v
 }
 
-// PartialFit processes the supplied training data (a variable number of strings
-// representing documents).  Each word appearing inside the training data will be
-// added to the Vocabulary.  Unlike Fit(), PartialFit() is intended to be called
-// multiple times to incrementally train the model and so is intended for online
-// or mini-batch training as opposed to batch training as with the Fit() method.
-func (v *CountVectoriser) PartialFit(train ...string) OnlineVectoriser {
-	i := len(v.Vocabulary)
-	v.fitVocab(i, train...)
-
-	return v
-}
-
 // fitVocab learns the vocabulary contained within the supplied training documents
 func (v *CountVectoriser) fitVocab(start int, train ...string) {
 	i := start

vectorisers_test.go

@@ -50,34 +50,6 @@ func TestCountVectoriserFit(t *testing.T) {
 		}
 	}
 }
-
-func TestCountVectoriserPartialFit(t *testing.T) {
-	var tests = []struct {
-		train     []string
-		stop      []string
-		vocabSize int
-	}{
-		{trainSet, []string{}, 26},
-		{trainSet[0:1], []string{}, 8},
-		{trainSet, stopWords, 18},
-	}
-
-	for testRun, test := range tests {
-		t.Logf("**** Test Run %d.\n", testRun+1)
-		vectoriser := NewCountVectoriser(test.stop...)
-
-		for _, v := range test.train {
-			vectoriser.PartialFit(v)
-		}
-
-		if len(vectoriser.Vocabulary) != test.vocabSize {
-			t.Logf("Expected training dataset %v of size %d but found vocabulary %v of size %d",
-				test.train, test.vocabSize, vectoriser.Vocabulary, len(vectoriser.Vocabulary))
-			t.Fail()
-		}
-	}
-}
-
 func TestCountVectoriserTransform(t *testing.T) {
 	var tests = []struct {
 		train     []string