ROC for SVM Model from ISLR
ROC
Performance Data
ISLR
Replications
yardstick
Gareth James
Daniela Witten
Trevor Hastie
Rob Tibshirani
The following example of Support Vector Machine is taken from Introduction to Statistical Learning: a great introductory book to Data Science by Gareth James, Daniela Witten, Trevor Hastie and Rob Tibshirani.
DCA for Quantifying the Additional Benefit of a New Marker by Emily Vertosick and Andrew Vickers
Replications
Decision
Emily Vertosick
Andrew Vickers
dcurves
rms
Hmisc
Prediction Model might gain accuracy if you’ll add more relevant features to existing models, but many times it’s not obvious what is the additional value of additional feature and how to quantify it in terms of Decision Making. The post Decision curve analysis for quantifying the additional benefit of a new marker by Emily Vertosick and Andrew Vickers show a simple example (the code presented here is almost identical to the original code presented in the link).
Precision Recall from Feature Engineering by Max Kuhn and Kjell Johnson
Replications
ROC
Precision Recall
Max Kuhn
Kjell Johnson
Feature Engineering by Max Kuhn and Kjell Johnson
yardstick
Precision Recall Curve is shown as an alternative to the known ROC curve in the “second part from the ‘Measuring Performance’ Chapter of Feature Engineering and Selection”. It is mentioned that this curve is more appropriate in terms of Information Retrieval.
Box-Cox transformation from Feature Engineering by Max Kuhn and Kjell Johnson
Replications
ROC
Max Kuhn
Kjell Johnson
Feature Engineering by Max Kuhn and Kjell Johnson
caret
This blog will be dedicated to the {rtichoke} package, which means that it will contain posts that are related to performance metrics and the possible related usability of {rtichoke}.
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