This chapter will serve as a reference for some of the most commonly used algorithms in Microsoft Azure Machine Learning. We will provide a brief introduction to algorithms such as linear regression, k-means for clustering, decision trees, boosted decision trees, neural networks, support vector machines, and Bayes point machines.
- Support Vector Machine
- Decision Tree
- Hide Node
- Ensemble Model
- Decision Tree Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Tax calculation will be finalised at checkout
Purchases are for personal use onlyLearn about institutional subscriptions
© 2015 Roger Barga, Valentine Fontama, and Wee Hyong Tok
About this chapter
Cite this chapter
Barga, R., Fontama, V., Tok, W.H. (2015). Introduction to Statistical and Machine Learning Algorithms. In: Predictive Analytics with Microsoft Azure Machine Learning. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-1200-4_6
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-1201-1
Online ISBN: 978-1-4842-1200-4