fcbf: Fast Correlation-Based Filter for Feature Selection
In dsnavega/cbfsr: cbfsr: Tools for correlation-based feature selection in R
Description
Usage
Arguments
Details
Value
Author(s)
References
Description
Fast Correlation-Based Filter for Feature Selection
Usage
1
fcbf(x, y)
Arguments
x
a symmetric numeric matrix with inter-correlation (association) of
the features (input) under study. See Details.
y
a vector with the correlation (association) of x (features) with the
class (output). See Details
Details
In this implementation, and following Hall (1999), correlation is used its
more general sense. Is up to the user to compute the matrix x and vector y
using the correlation / association measure that best suite the data and
problem at hand.
Value
a logical vector of selected features
Author(s)
David Senhora Navega
References
Hall, M.A., 1999. Correlation-based feature selection for machine learning.
Yu, L. and Liu, H., 2003. Feature selection for high-dimensional data:
A fast correlation-based filter solution. In Proceedings of the
20th international conference on machine learning (ICML-03) (pp. 856-863).
dsnavega/cbfsr documentation built on Jan. 1, 2021, 12:07 a.m.
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Description Usage Arguments Details Value Author(s) References
Description
Fast Correlation-Based Filter for Feature Selection
Usage
1 | fcbf(x, y)
|
Arguments
x |
a symmetric numeric matrix with inter-correlation (association) of the features (input) under study. See Details. |
y |
a vector with the correlation (association) of x (features) with the class (output). See Details |
Details
In this implementation, and following Hall (1999), correlation is used its more general sense. Is up to the user to compute the matrix x and vector y using the correlation / association measure that best suite the data and problem at hand.
Value
a logical vector of selected features
Author(s)
David Senhora Navega
References
Hall, M.A., 1999. Correlation-based feature selection for machine learning.
Yu, L. and Liu, H., 2003. Feature selection for high-dimensional data: A fast correlation-based filter solution. In Proceedings of the 20th international conference on machine learning (ICML-03) (pp. 856-863).
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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