Figure 6From: A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral dataChannel-wise variance of each feature (horizontal axis) and its correlation with the dependent variable (vertical axis). For the data sets of the left and the central column, a feature selection was not required for optimal performance, while the data sets shown in the right columns benefitted from a feature selection. Circle diameter indicates magnitude of the coefficient in the PLS regression. In the right column selected features are shown by red circles, while (the original values of) eliminated features are indicated by black dots. Relevant features show both a high variance and correlation with the class labels.Back to article page