Hub
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Hub
  • Nodes
  • Rank Correlation
NodeNode / Other

Rank Correlation

Analytics Statistics
Drag & drop
Like
Copy short link

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. The node uses fractional ranks for equal values. 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. For Spearman's rank correlation coefficient the p-value and degrees of freedom are computed. The p-value indicates the probability of an uncorrelated system producing a correlation at least as extreme, if the mean of the correlation is zero and it follows a t-distribution with df degrees of freedom.
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.

Node details

Input ports
  1. Type: Table
    Numeric input data
    Numeric input data to evaluate
Output ports
  1. Type: Table
    Correlation measure
    Correlation variables, p-values and degrees of freedom.
  2. Type: Table
    Correlation matrix
    Correlation variables in a matrix representation.
  3. Type: Correlation
    Correlation model
    A model containing the correlation measures. This model is appropriate to be read by the Correlation Filter node.
  4. Type: Table
    Rank table
    A table containing the fractional ranks of the columns. Where the rank corresponds to the values position in a sorted table.

Extension

The Rank Correlation node is part of this extension:

  1. Go to item

Related workflows & nodes

  1. Go to item
    Linear correlation
    There has been no description set for this workflow's metadata.
    mlauber71 > Public > forum > kn_forum_correlation
  2. Go to item
    Read an XLS file
    Reading XLS Excel
    +1
    There are multiple ways of reading an .xls file. 1. Add the XLS Reader to the workspace a…
    jose_barboza > Public > Regresion_Lineal_desde_XLS
  3. Go to item
    Экзамен Nekrasova
    liza > Public > Экзамен Nekrasova
  4. Go to item
    column_correlation_analysis
    lukass > Forum > column_correlation_analysis
  5. Go to item
    Linear Regression to calculate Price of a Lego set
    Linear regression Machine learning Data science
    +2
    The workflow trains a Linear Regression model to predict the price of a Lego set based on…
    swantikag > Public > LinearRegression-LegoSet > LinearRegressionModel > LinearRegression-LegoSet
  6. Go to item
    testing_group
    johanna_alm > Public > testing_group
  7. Go to item
    Assessment of Vina for SARS-CoV-2 Main Protease
    Drug Discovery Drug Design Cheminformatics
    +5
    There has been no description set for this workflow's metadata.
    arashsadri > Biological Sciences and Physics Unified Internal Evolution and Urging the Second Scientific Revolution > Assessment of Vina for SARS-CoV-2 Main Protease
  8. Go to item
    05-k-means-wine-template
    thagen > ml2 > templates > 05-k-means-wine-template
  9. Go to item
    Wahl und Wirtschaft - Verfügbares Einkommen und Zweitstimmenergebnisse zur Bundestagswahl 2021 (Deutschland) - Korrelationskoeffizienten
    Spearman Korrelation Bundestagswahl
    +1
    Wahl und Wirtschaft - Verfügbares Einkommen und Zweitstimmenergebnisse zur Bundestagswahl…
    mlauber71 > Forum > 2021 > wahl_und_wirtschaft_btw2021 > m_050_wahlstatistik_2021_verfuegbares_einkommen
  10. Go to item
    Journal2_Perfomance-Injuries
    airvag > Public > Journal2_Perfomance-Injuries

No known nodes available

KNIME
Open for Innovation

KNIME AG
Hardturmstrasse 66
8005 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • E-Learning course
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • KNIME Open Source Story
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more on KNIME Server
© 2022 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits