lgm_yhat: Implementations for Logistic Regression Compute yhat for...
In tbonza/supml: "Algorithms for Supervised Machine Learning"
Description
Usage
Arguments
Value
Description
Implementations for Logistic Regression
Compute yhat for logistic regression
Usage
1
Arguments
w
vector of weights
X
matrix of predictors
Value
dot product of X and w with sigmoid function
tbonza/supml documentation built on May 17, 2019, 3:14 a.m.
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Description Usage Arguments Value
Description
Implementations for Logistic Regression Compute yhat for logistic regression
Usage
1 |
Arguments
w |
vector of weights |
X |
matrix of predictors |
Value
dot product of X and w with sigmoid function
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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