model_oclr: One-class logistic regression
In ArtemSokolov/gelnet: Generalized Elastic Nets
Description
Usage
Arguments
Details
Value
Description
Defines a one-class logistic regression (OCLR) task
Usage
1
model_oclr(nonneg = FALSE)
Arguments
nonneg
set to TRUE to enforce non-negativity constraints on the weights (default: FALSE)
Details
The OCLR objective function is defined as
-\frac{1}{n} ∑_i s_i - \log( 1 + \exp(s_i) ) + R(w)
where
s_i = w^T x_i
Value
A GELnet task definition that can be combined with gelnet() output
ArtemSokolov/gelnet documentation built on Sept. 13, 2019, 4:01 a.m.
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Description Usage Arguments Details Value
Description
Defines a one-class logistic regression (OCLR) task
Usage
1 | model_oclr(nonneg = FALSE)
|
Arguments
nonneg |
set to TRUE to enforce non-negativity constraints on the weights (default: FALSE) |
Details
The OCLR objective function is defined as
-\frac{1}{n} ∑_i s_i - \log( 1 + \exp(s_i) ) + R(w)
where
s_i = w^T x_i
Value
A GELnet task definition that can be combined with gelnet() output
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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