my_knn_cv: k-Nearest Neighbors Cross-Validation
In SabrinaYuY/project3: PACKAGE FOR PROJECT 3 PART1
Description
Usage
Arguments
Value
Examples
Description
Predict output class species using covariates
bill_length_mm, bill_depth_mm, flipper_length_mm, and body_mass_g.
Usage
1
my_knn_cv(train, cl, k_nn, k_cv)
Arguments
train:
input data frame.
cl:
true class value of your training data.
k_nn:
integer representing the number of neighbors.
k_cv:
integer representing the number of folds.
Value
class: a vector of the predicted class Ŷ i for all observation.
cv_err: a numeric with the cross-validation misclassification error.
Examples
1
my_knn_cv(data_peng, test, k_nn = 1, k_cv = 5)
SabrinaYuY/project3 documentation built on Dec. 18, 2021, 12:02 p.m.
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Description Usage Arguments Value Examples
Description
Predict output class species using covariates bill_length_mm, bill_depth_mm, flipper_length_mm, and body_mass_g.
Usage
1 | my_knn_cv(train, cl, k_nn, k_cv)
|
Arguments
train: |
input data frame. |
cl: |
true class value of your training data. |
k_nn: |
integer representing the number of neighbors. |
k_cv: |
integer representing the number of folds. |
Value
class: a vector of the predicted class Ŷ i for all observation.
cv_err: a numeric with the cross-validation misclassification error.
Examples
1 | my_knn_cv(data_peng, test, k_nn = 1, k_cv = 5)
|
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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