Figure 5From: A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral dataClassification accuracy (left column) and standard error (right column) during the course of recursive feature elimination for PLS regression (black), PC regression (dark gray) and random forest (light gray), in combination with different feature selection criteria: univariate (dotted), PLS/PC regression (dashed) and Gini importance (solid).Back to article page