laplacian_score: Laplacian scoring for variables
In james-gyzhu/feature_selection: Significance scoring for variables
Description
Usage
Arguments
Value
Description
Laplacian scoring for variables
Usage
1
2
laplacian_score(x, stand = FALSE, affin_method = "euclidean",
max_core_num = getOption("max_core_num", 2L))
Arguments
x
a data frame or matrix, row-wised input varible data for scoring
stand
a logical value indicating if the varibles to be scaled
affin_method
distance measure for affinity matrix calculation
max_core_num
integer, number of cores/threads used for parallelized clustering
Value
a data frame with significance scores for the variables
james-gyzhu/feature_selection documentation built on May 18, 2019, 11:19 a.m.
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Description Usage Arguments Value
Description
Laplacian scoring for variables
Usage
1 2 | laplacian_score(x, stand = FALSE, affin_method = "euclidean",
max_core_num = getOption("max_core_num", 2L))
|
Arguments
x |
a data frame or matrix, row-wised input varible data for scoring |
stand |
a logical value indicating if the varibles to be scaled |
affin_method |
distance measure for affinity matrix calculation |
max_core_num |
integer, number of cores/threads used for parallelized clustering |
Value
a data frame with significance scores for the variables
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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