Corrmap: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
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:order = corrmap(data,labels,''reord'') | :order = corrmap(data,labels,''reord'') | ||
:order = corrmap(data,reord) | :order = corrmap(data,reord) | ||
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CORRMAP produces a pseudocolor map that shows the correlation between variables (columns) in a data set. The function will reorder the variables by KNN clustering if desired. | CORRMAP produces a pseudocolor map that shows the correlation between variables (columns) in a data set. The function will reorder the variables by KNN clustering if desired. | ||
The input is the data data class "double" or "dataset". | The input is the data (data) class "double" or "dataset". | ||
Optional input (''labels'') contains the variable labels when the data is class "double". | |||
Optional input '' | Optional input (''reord'') will cause CORRMAP to keep the original ordering of the variables if set to 0. | ||
The output (order) is a vector of indices with the variable ordering. | |||
===Examples=== | |||
corrmap(data,labels) produces a | corrmap(data,labels) | ||
produces a pseudocolor correlation map with variable reordering. | |||
corrmap(data,labels,0) produces a | corrmap(data,labels,0) | ||
produces a pseudocolor correlation map without variable reordering. | |||
===See Also=== | ===See Also=== | ||
[[autocor]], [[crosscor]] | [[autocor]], [[crosscor]], [[xycorrcoef]] | ||
Latest revision as of 14:59, 16 December 2019
Purpose
Correlation map with variable regrouping.
Synopsis
- order = corrmap(data,labels,reord)
- order = corrmap(data,reord)
Description
CORRMAP produces a pseudocolor map that shows the correlation between variables (columns) in a data set. The function will reorder the variables by KNN clustering if desired.
The input is the data (data) class "double" or "dataset".
Optional input (labels) contains the variable labels when the data is class "double".
Optional input (reord) will cause CORRMAP to keep the original ordering of the variables if set to 0.
The output (order) is a vector of indices with the variable ordering.
Examples
corrmap(data,labels)
produces a pseudocolor correlation map with variable reordering.
corrmap(data,labels,0)
produces a pseudocolor correlation map without variable reordering.