multi_logistic_regression: a classification model genralizing logistic regression to...
In cz354/bis557: The package for bis557's homework
Description
Usage
Arguments
Examples
View source: R/multi-logistic-regression.r
Description
a classification model genralizing logistic regression to accommodate more than two classes.
Usage
1
multi_logistic_regression(X, Y, maxit = 10000, tol = 1e-20)
Arguments
X
data matrix
Y
Response vector
maxit
Default is 10000. The maximum number of iterations.
tol
Default is 1e-20. The minimum difference between the old beta and the update beta.
Examples
1
2
3
4
data("iris")
X = iris[,-5]
Y=iris$Species
multi_logistic_regression(X,Y)
cz354/bis557 documentation built on Dec. 20, 2020, 3:05 a.m.
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Description Usage Arguments Examples
View source: R/multi-logistic-regression.r
Description
a classification model genralizing logistic regression to accommodate more than two classes.
Usage
1 | multi_logistic_regression(X, Y, maxit = 10000, tol = 1e-20)
|
Arguments
X |
data matrix |
Y |
Response vector |
maxit |
Default is 10000. The maximum number of iterations. |
tol |
Default is 1e-20. The minimum difference between the old beta and the update beta. |
Examples
1 2 3 4 | data("iris")
X = iris[,-5]
Y=iris$Species
multi_logistic_regression(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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