find_k: A MVDA Function
In angy89/MVDA_package: Multi-View Biological Data Analysis
Description
Usage
Arguments
Value
Description
This function calculates the best value of k through a series of executions (from kmin to kmax) of the algorithm of factorization in each step calculates the entropy of the matrix P of Responsibilities and chooses the partition with greater entropy value
Usage
1
find_k(kmin, kmax, X, eps)
Arguments
kmin
is the value of k from wich it start to search
kmax
is the maximum value of k
X
is the matrix resulting from the concatenation of the membership matrix for each view
eps
is the precision parameter
Value
the best factorization and the optimum value of k
angy89/MVDA_package documentation built on May 7, 2019, 8:58 p.m.
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Description Usage Arguments Value
Description
This function calculates the best value of k through a series of executions (from kmin to kmax) of the algorithm of factorization in each step calculates the entropy of the matrix P of Responsibilities and chooses the partition with greater entropy value
Usage
1 | find_k(kmin, kmax, X, eps)
|
Arguments
kmin |
is the value of k from wich it start to search |
kmax |
is the maximum value of k |
X |
is the matrix resulting from the concatenation of the membership matrix for each view |
eps |
is the precision parameter |
Value
the best factorization and the optimum value of k
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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