Abstract
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.
Keywords
- 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.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsAuthor information
Authors and Affiliations
Rights and permissions
Copyright information
© 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
Download citation
DOI: 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
eBook Packages: Professional and Applied ComputingProfessional and Applied Computing (R0)Apress Access Books