Ω(err).ShouldNot(HaveOccurred()) }) Context("Given a dataset with non-float features", func() { BeforeEach(func() { columnTypes, err := columntype.StringsToColumnTypes([]string{"x", "1.0"}) Ω(err).ShouldNot(HaveOccurred()) trainingSet = dataset.NewDataset([]int{0}, []int{1}, columnTypes) err = trainingSet.AddRowFromStrings([]string{"hi", "24"}) Ω(err).ShouldNot(HaveOccurred()) }) It("Returns an error", func() { err := estimator.Train(trainingSet) Ω(err).Should(BeAssignableToTypeOf(gdeErrors.NonFloatFeaturesError{})) }) }) Context("Given a dataset with a non-float target", func() { BeforeEach(func() { columnTypes, err := columntype.StringsToColumnTypes([]string{"x", "1.0"}) Ω(err).ShouldNot(HaveOccurred()) trainingSet = dataset.NewDataset([]int{1}, []int{0}, columnTypes) err = trainingSet.AddRowFromStrings([]string{"hi", "24"}) Ω(err).ShouldNot(HaveOccurred()) })