EuclideanProjectionENNORM: Euclidean projection on elastic net
In AMOUNTAIN: Active modules for multilayer weighted gene co-expression networks: a continuous optimization approach
Description
Usage
Arguments
Value
Author(s)
References
Examples
Description
Piecewise root finding algorithm for Euclidean projection on elastic net
Usage
1
EuclideanProjectionENNORM(y, t, alpha = 0.5)
Arguments
y
constant vector
t
radius of elastic net ball
alpha
parameter in elastic net: alpha x_1 + (1-alpha)*x_2^2=t
Value
a list containing network adjacency matrix, node score and module membership
Author(s)
Dong Li, dxl466@cs.bham.ac.uk
References
Gong, Pinghua, Kun Gai, and Changshui Zhang. "Efficient euclidean projections via piecewise root finding and its application in gradient projection." Neurocomputing 74.17 (2011): 2754-2766.
Examples
1
2
3
y=rnorm(100)
x=EuclideanProjectionENNORM(y,1,0.5)
sparistyx = sum(x==0)/100
AMOUNTAIN documentation built on Nov. 8, 2020, 5:28 p.m.
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Description Usage Arguments Value Author(s) References Examples
Description
Piecewise root finding algorithm for Euclidean projection on elastic net
Usage
1 | EuclideanProjectionENNORM(y, t, alpha = 0.5)
|
Arguments
y |
constant vector |
t |
radius of elastic net ball |
alpha |
parameter in elastic net: alpha x_1 + (1-alpha)*x_2^2=t |
Value
a list containing network adjacency matrix, node score and module membership
Author(s)
Dong Li, dxl466@cs.bham.ac.uk
References
Gong, Pinghua, Kun Gai, and Changshui Zhang. "Efficient euclidean projections via piecewise root finding and its application in gradient projection." Neurocomputing 74.17 (2011): 2754-2766.
Examples
1 2 3 | y=rnorm(100)
x=EuclideanProjectionENNORM(y,1,0.5)
sparistyx = sum(x==0)/100
|
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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