multiclass_hw3c: Multi-Class Logistic Regression
In brian-d1018/bis557: Brian's BIS 557 Work
Description
Usage
Arguments
Value
Examples
View source: R/multiclass_hw3c.R
Description
This function classifies observations for multiple classes.
This algorithm will use the "one-vs-all" approach.
Usage
1
multiclass_hw3c(X, y, maxiter = 50, tol = 1e-12)
Arguments
X
Numeric (continuous or categorical) data matrix
y
Categorical Response/Target vector (should be a factor)
maxiter
Maximum number of iterations
tol
Tolerance
Value
The predicted class/category for each observation
Examples
1
2
brian-d1018/bis557 documentation built on Dec. 17, 2020, 6:21 p.m.
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Description Usage Arguments Value Examples
View source: R/multiclass_hw3c.R
Description
This function classifies observations for multiple classes. This algorithm will use the "one-vs-all" approach.
Usage
1 | multiclass_hw3c(X, y, maxiter = 50, tol = 1e-12)
|
Arguments
X |
Numeric (continuous or categorical) data matrix |
y |
Categorical Response/Target vector (should be a factor) |
maxiter |
Maximum number of iterations |
tol |
Tolerance |
Value
The predicted class/category for each observation
Examples
1 2 |
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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