Rank Correlation

This Node Is Deprecated — This version of the node has been replaced with a new and improved version. The old version is kept for backwards-compatibility, but for all new workflows we suggest to use the version linked below.

Calculates for each pair of selected columns a correlation coefficient, i.e. a measure of the correlation of the two variables.

All measures are based on the rank of the cells. Where the rank of a cell value refers to its position in a sorted list of all entries. All correlation can be calculated on any kind of DataColumn. However please note that we use the default ordering of the values. If there is no ordering defined in the column, a string representation will be used. Spearman's rank correlation coefficient is a statistical measure of the strength of a monotonic relationship between paired data. Where the monotonic relationship is characterised by a relationship between ordered sets that preserves the given order, i.e., either never increases or never decreases as its independent variable increases. The value of this measure ranges from -1 (strong negative correlation) to 1 (strong positive correlation). A perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other. Goodman and Kruskal's gamma as well as Kendall's tau rank correlation coefficient is used to measure the strength of association between two measured quantities. Both are based on the number of concordant and discordant pairs. Kendall's Tau A and Tau B coefficients can be considered as standardized forms of Gamma. The difference between Tau A and Tau B is that Tau A statistic does not consider tied values, while Tau B makes adjustments for them. By tied observations we consider two or more observations having the same value. Both Kruskal's gamma and Kendall's Tau A are mostly suitable for square tables, whereas Tau B is most appropriately used for rectangular tables. The coefficients must be in the range from −1 (100% negative association, or perfect inversion) to +1 (100% positive association, or perfect agreement). A value of zero indicates the absence of association.

Rows containing Missing Values will be ignored, not used for the calculations. For other behaviors please resolve them before.

Options

Correlation Type: Chose the type of correlation here. There are the Spearman Correlation, two types of Kendalls Tau and Goodman and Kruskal's Gamma.

Manual Selection

Include: This list contains the names of those columns in the input table for which correlation values should be computed.
Exclude: This list contains the names of those columns in the input table to be left out of the computation.
Filter: Use one of these fields to filter either the Include or Exclude list for certain column names or name substrings.
Buttons: Use these buttons to move columns between the Include and Exclude list. Single-arrow buttons will move all selected columns. Double-arrow buttons will move all columns (filtering is taken into account).
Enforce Exclusion: Select this option to enforce the current exclusion list to stay the same even if the input table specification changes. If some of the excluded columns are not available anymore, a warning is displayed. (New columns will automatically be added to the inclusion list.)
Enforce Inclusion: Select this option to enforce the current inclusion list to stay the same even if the input table specification changes. If some of the included columns are not available anymore, a warning is displayed. (New columns will automatically be added to the exclusion list.)

Wildcard/Regex Selection

Pattern: Type a search pattern which matches columns to move into the Include or Exclude list. Which list is used can be specified. You can use either Wildcards ('?' matching any character, '*' matching a sequence of any characters) or Regex. You can specify whether your pattern should be case sensitive.

Type Selection

Type List: Select the column types that you want to include. Column types that are currently not present are depicted in italic.

Input Ports

: Numeric input data to evaluate

Output Ports

: Correlation variables in a square matrix
: A model containing the correlation measures. This model is appropriate to be read by the Correlation Filter node.
: A table containing the ranks of the columns. Where the rank corresponds to the values position in a sorted table.

Popular Predecessors

Popular Successors

Views

Correlation Matrix: Squared table view showing the pair-wise correlation values of all columns. The color range varies from dark red (strong negative correlation), over white (no correlation) to dark blue (strong positive correlation). If a correlation value for a pair of column is not available, the corresponding cell contains a missing value (shown as cross in the color view).

Workflows

Developers

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Installation

To use this node in KNIME, install the extension KNIME Statistics Nodes from the below update site following our NodePit Product and Node Installation Guide:

v5.4

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.4.0.v202408311922

On NodePit since: 2024-12-06

Last update: 2024-12-17

Tags: Deprecated

KNIME versions: Since v3.6

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