RCV: RCV
In MiriamEsteve/EAT: Efficiency Analysis Trees
Description
Usage
Arguments
Value
View source: R/pruningScoring.R
Description
RCV
Usage
1
RCV(N, Lv, y, alphaIprim, fold, TAiv)
Arguments
N
Number of rows in data.
Lv
Test set.
y
Column output indexes in data.
alphaIprim
Alpha obtained as the square root of the product of two consecutive alpha values in tree_alpha list. It is used to find the best pruning tree.
fold
Parts in which the original data is divided into to perform Cross-Validation.
TAiv
List with each possible pruning for the deep tree generated with the train set and its associated alpha values.
Value
Set of best pruning and the associated error calculated with test sets.
MiriamEsteve/EAT documentation built on Jan. 18, 2022, 6:55 p.m.
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Description Usage Arguments Value
View source: R/pruningScoring.R
Description
RCV
Usage
1 | RCV(N, Lv, y, alphaIprim, fold, TAiv)
|
Arguments
N |
Number of rows in data. |
Lv |
Test set. |
y |
Column output indexes in data. |
alphaIprim |
Alpha obtained as the square root of the product of two consecutive alpha values in tree_alpha list. It is used to find the best pruning tree. |
fold |
Parts in which the original data is divided into to perform Cross-Validation. |
TAiv |
List with each possible pruning for the deep tree generated with the train set and its associated alpha values. |
Value
Set of best pruning and the associated error calculated with test sets.
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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