export_filters: Export filters
In mRMRe: Parallelized Minimum Redundancy, Maximum Relevance (mRMR)
export_filters R Documentation
Export filters
Description
Export the filters
Arguments
childrenCountPerLevel
...
dataMatrix
...
priorsMatrix
...
priorsWeight
...
sampleStrata
...
sampleWeights
...
featureTypes
...
sampleCount
...
featureCount
...
sampleStratumCount
...
targetFeatureIndices
...
continuousEstimator
...
outX
...
bootstrapCount
...
miMatrix
...
Value
Exhaustively computes the minimum redudancy maximim relevance features from
the mutual information matrix, returing a list of solutions where each item
is a numeric index of selected features.
Author(s)
Nicolas De Jay, Simon Papillon-Cavanagh, Benjamin Haibe-Kains
mRMRe documentation built on April 25, 2023, 9:13 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| export_filters | R Documentation |
Export filters
Description
Export the filters
Arguments
childrenCountPerLevel |
... |
dataMatrix |
... |
priorsMatrix |
... |
priorsWeight |
... |
sampleStrata |
... |
sampleWeights |
... |
featureTypes |
... |
sampleCount |
... |
featureCount |
... |
sampleStratumCount |
... |
targetFeatureIndices |
... |
continuousEstimator |
... |
outX |
... |
bootstrapCount |
... |
miMatrix |
... |
Value
Exhaustively computes the minimum redudancy maximim relevance features from the mutual information matrix, returing a list of solutions where each item is a numeric index of selected features.
Author(s)
Nicolas De Jay, Simon Papillon-Cavanagh, Benjamin Haibe-Kains
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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