README.md

In tbonza/supml: "Algorithms for Supervised Machine Learning"

supml

Supervised machine learning algorithms -- excluding neural networks. These algorithms are based off of class assignments. This means the algorithms have been largely designed and used from a research perspective. However, we do try to use efficient operations whenever possible; such as vectorization.

See R documentation for basic usage.

Naive Bayes Classifier for Spatial Data

This model is in the pre-release phase. You will need devtools in order to use it.

devtools::test()
devtools::document()
devtools::install()

References

The documentation references three textbooks using the abbreviations JW, HT, and CB:

• (JW) An Introduction to Statistical Learning. G. James, D. Witten, T. Hastie, R. Tibshirani, Springer 2013.
• (HT) Elements of Statistical Learning. T. Hastie, R. Tibshirani and J. Friedman, Springer, 2009.
• (CB) Pattern Recognition and Machine Learning. C. M. Bishop, Springer 2006.

tbonza/supml documentation built on May 17, 2019, 3:14 a.m.