model_perfs_training_set1000: Model performances in the training set based on 1000...
In bennysalo/predict-recidivism: Analyses for prediction of recidivism in Finnish data using supervised learning
Description
Usage
Format
Details
Source
Description
This a data object of class resamples generated by
caret::resamples that contains the model performance of all models in
the training set based on 250 resamples of a 4-fold cross-validation. Model names can be looked up
model_grid.
Usage
1
Format
An object of class resamples of length 6.
Details
The performance metrics are:
- d_AUC: Cohen's d based on a naive transformation from Area Under Curve
- E_O_ratio
- logLoss
- McF_R2: McFadden's Pseudo R^2
- ROC: Area Under Curve from a receiver operating characteristic curve.
Source
The data object is created in
"data-raw/06_model_perfs_training_set.Rmd". See also
"data-raw/00_About_data_raw.Rmd"
bennysalo/predict-recidivism documentation built on May 29, 2019, 10:34 a.m.
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Description Usage Format Details Source
Description
This a data object of class resamples generated by
caret::resamples that contains the model performance of all models in
the training set based on 250 resamples of a 4-fold cross-validation. Model names can be looked up
model_grid.
Usage
1 |
Format
An object of class resamples of length 6.
Details
The performance metrics are: - d_AUC: Cohen's d based on a naive transformation from Area Under Curve - E_O_ratio - logLoss - McF_R2: McFadden's Pseudo R^2 - ROC: Area Under Curve from a receiver operating characteristic curve.
Source
The data object is created in "data-raw/06_model_perfs_training_set.Rmd". See also "data-raw/00_About_data_raw.Rmd"
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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