def test_append_bias_with_sp_vector(self): data = Vectors.sparse(3, {0: 2.0, 2: 2.0}) expected = Vectors.sparse(4, {0: 2.0, 2: 2.0, 3: 1.0}) # Returned value must be SparseVector ret = MLUtils.appendBias(data) self.assertEqual(ret, expected) self.assertEqual(type(ret), SparseVector)
def test_append_bias_with_sp_vector(self): data = Vectors.sparse(3, {0: 2.0, 2: 2.0}) expected = Vectors.sparse(4, {0: 2.0, 2: 2.0, 3: 1.0}) # Returned value must be SparseVector ret = MLUtils.appendBias(data) self.assertEqual(ret, expected) self.assertEqual(type(ret), SparseVector)
def test_append_bias_with_vector(self): data = Vectors.dense([2.0, 2.0, 2.0]) ret = MLUtils.appendBias(data) self.assertEqual(ret[3], 1.0) self.assertEqual(type(ret), DenseVector)
def test_append_bias(self): data = [2.0, 2.0, 2.0] ret = MLUtils.appendBias(data) self.assertEqual(ret[3], 1.0) self.assertEqual(type(ret), DenseVector)
def test_append_bias_with_vector(self): data = Vectors.dense([2.0, 2.0, 2.0]) ret = MLUtils.appendBias(data) self.assertEqual(ret[3], 1.0) self.assertEqual(type(ret), DenseVector)
def test_append_bias(self): data = [2.0, 2.0, 2.0] ret = MLUtils.appendBias(data) self.assertEqual(ret[3], 1.0) self.assertEqual(type(ret), DenseVector)