Kao-Tai Tsai

Machine Learning for Knowledge Discovery with R

Methodologies for Modeling, Inference and Prediction

• Gebundenes Buch

Produktbeschreibung

'Machine Learning for Knowledge Discovery with R' contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes most recent supervised and unsupervised machine learning methodologies

Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 244
• Erscheinungstermin: 15. September 2021
• Englisch
• Abmessung: 234mm x 156mm x 16mm
• Gewicht: 544g
• ISBN-13: 9781032065366
• ISBN-10: 1032065362
• Artikelnr.: 62231368

Autorenporträt

Kao-Tai Tsai obtained his Ph.D. in Mathematical Statistics from University of California, San Diego and had worked at AT&T Bell Laboratories to conduct statistical research, modelling, and exploratory data analysis. After that, he joined the US FDA and later pharmaceutical companies focusing on biostatistics, clinical trial research and data analysis to address the unmet needs in human health.

Inhaltsangabe

1. Statistical Data Analysis. 2. Examining Data Distribution. 3. Regression
with Shrinkage. 4. Recursive Partitioning Modeling. 5. Support Vector
Machines. 6. Cluster Analysis. 7. Neural Networks. 8. Causal Inference and
Matching. 9. Business and Commercial Data Modeling. 10. Analysis of
Response Profiles.