Linear 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.
Go to Suggested ReplacementLinear Correlation

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

Which correlation measure is applied depends on the types of the underlying variables:
numeric <-> numeric: Pearson's product-moment coefficient. Missing values in such columns are ignored (the corresponding records are skipped). The value of this measure ranges from -1 (strong negative correlation) to 1 (strong positive correlation). A value of 0 represents no correlation.
nominal <-> nominal: Pearson's chi square test on the contingency table. This value is then normalized to a range [0,1] using Cramer's V, whereby 0 represents no correlation and 1 a strong correlation. Missing values in nominal columns are treated such as they were a self-contained possible value. If one of the two columns contains more possible values than specified in the dialog (default 50), the correlation will not be computed.
Correlation measures for other pairs of columns are not available, they are represented by missing values in the output table and crosses in the accompanying view.


Column Filter
Select columns for which correlation values shall be computed.
Possible Values Count
Select an upper bound for the number of possible values for each of the nominal columns. If more values are encountered in a nominal column, the column will be ignored (no correlation values will be computed).

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.

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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).


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