Lantz Machine Learning with R

Expert techniques for predictive modeling to solve all your data analysis problems
2. Auflage 2015
ISBN: 978-1-78439-452-3
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 452 Seiten

No detailed description available for "Machine Learning with R".

Autoren/Hrsg.

Lantz, Brett

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik

Inhaltsverzeichnis

Table of Contents - Introducing Machine Learning
- Managing and Understanding Data
- Lazy Learning: Classification using Nearest Neighbors
- Probabilistic Learning: Classification using Na
- Divide and Conquer: Classification using Trees and Rules
- Forecasting Numeric Data: Regression Methods
- Black Box Methods: Neural Networks and Support Vector Machines
- Finding Patterns: Market Basket Analysis Using Association Rules
- Finding Groups of Data: Clustering with k-means
- Evaluating Model Performance
- Improving Model Performance
- Specialized Machine Learning Topics

Über Autor(innen)

Lantz Brett:

Brett Lantz (DataSpelunking) has spent more than 10 years using innovative data methods to understand human behavior. A sociologist by training, Brett was first captivated by machine learning during research on a large database of teenagers' social network profiles. Brett is a DataCamp instructor and a frequent speaker at machine learning conferences and workshops around the world. He is known to geek out about data science applications for sports, autonomous vehicles, foreign language learning, and fashion, among many other subjects, and hopes to one day blog about these subjects at Data Spelunking, a website dedicated to sharing knowledge about the search for insight in data.