december 2015 ieee Geoscience and remote sensing magazine 29 R Snippet Type Conversion (a) Cluster Colour Selection EDA KNIME Table Output Scatter Plot Type Conversion Plot Classified Clusters Sorter Table To R R View (Workspace) Sort by ID Table Assign Value Create Column ID MI Rasterization Interactive Table String To Number Color Manager Split Column Regex Split Missing Value RowID EDA KNIME Table Output Scatter Plot Plot Classified Cluster Table To R R View (Workspace) Figure 1. KNIME workflow developed to classify geological discontinuities in a selected region. A) KNIME nodes used to perform unsupervised classification of a combination of gravity and magnetic airborne surveys. B) Result of k-Means cluster analysis based on 11 partitions displaying pseudo-geology. C) Result of Fuzzy c-Means cluster analysis (see text for a more detailed explanation of the algorithms). (Continued) Data Clustering Joiner Cluster Colour Selection Color Manager Row Combination (Outer Join) Data Clustering Fuzzy c-Means Remove MI Rows Missing Value Import of ASCII Data Normalization Rasters R Source (Table) k-Means Sorter Sort by ID Assign Value Create Table MI Rasterization Column ID Interactive Table String To Number Regex Split Missing Value RowID Split Row Column Combination (Outer Join) Joiner