fastLogisticModel: Logistic Regression Fitting Using L-BFGS Algorithm
In RcppLbfgsBlaze: 'L-BFGS' Algorithm Based on 'Blaze' for 'R' and 'Rcpp'
fastLogisticModel R Documentation
Logistic Regression Fitting Using L-BFGS Algorithm
Description
This function leverage blaze and LBFGS-Blaze to efficiently fit logistic regression.
Usage
fastLogisticModel(X, y)
Arguments
X
The model matrix.
y
The response vector.
Value
A list of L-BFGS optimization result.
Examples
X <- matrix(rnorm(5000), 1000)
coef <- runif(5, -3, 3)
y <- sapply(1 / (1 + exp(-X %*% coef)), function(p) rbinom(1, 1, p), USE.NAMES = FALSE)
fit <- fastLogisticModel(X, y)
RcppLbfgsBlaze documentation built on May 29, 2024, 2:45 a.m.
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| fastLogisticModel | R Documentation |
Logistic Regression Fitting Using L-BFGS Algorithm
Description
This function leverage blaze and LBFGS-Blaze to efficiently fit logistic regression.
Usage
fastLogisticModel(X, y)
Arguments
X |
The model matrix. |
y |
The response vector. |
Value
A list of L-BFGS optimization result.
Examples
X <- matrix(rnorm(5000), 1000)
coef <- runif(5, -3, 3)
y <- sapply(1 / (1 + exp(-X %*% coef)), function(p) rbinom(1, 1, p), USE.NAMES = FALSE)
fit <- fastLogisticModel(X, y)
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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