ranked_models: Fit the models and rank them by their fitness.
In kunaljaydesai/GA: Implement Genetic Variable Selection Algorithm
Description
Usage
Arguments
Value
Examples
Description
Fit the models and rank them by their fitness.
Usage
1
2
ranked_models(index, X, y, fit_func = AIC, family = gaussian,
cluster = NA)
Arguments
index
A list of indices of selected variables.
X
Data frame of all features
y
Dependent variable
fit_func
Function for fitness measurement. Default is AIC.
family
A description of the family of distributions to be used.
Value
a data frame containing index list and their respective fitness, sorted by fitness in ascending order
Examples
1
2
3
4
X <- mtcars[-1]
y <- unlist(mtcars[1])
index <-initialize_parents(10,20)$index
ranked_models(index, X, y)
kunaljaydesai/GA documentation built on May 28, 2019, 7:38 a.m.
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Description Usage Arguments Value Examples
Description
Fit the models and rank them by their fitness.
Usage
1 2 | ranked_models(index, X, y, fit_func = AIC, family = gaussian,
cluster = NA)
|
Arguments
index |
A list of indices of selected variables. |
X |
Data frame of all features |
y |
Dependent variable |
fit_func |
Function for fitness measurement. Default is AIC. |
family |
A description of the family of distributions to be used. |
Value
a data frame containing index list and their respective fitness, sorted by fitness in ascending order
Examples
1 2 3 4 | X <- mtcars[-1]
y <- unlist(mtcars[1])
index <-initialize_parents(10,20)$index
ranked_models(index, 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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