Machine learning for knowledge discovery with R : methodologies for modeling, inference and prediction / Kao-Tai Tsai.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9781032065366
- 9781032071596
- 006.32 23 TSA
Item type | Current library | Home library | Call number | Status | Date due | Barcode | |
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Dept. of Computer Science Reference | Dept. of Computer Science | 006.32 TSA (Browse shelf(Opens below)) | Available | DCS4924 |
Includes bibliographical references and index.
"Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling, regularized regression, support vector machine, neural network, clustering, and causal-effect inference. Additionally, it emphasizes statistical thinking of data analysis, use of statistical graphs for data structure exploration, and result presentations. The book includes many real-world data examples from life-science, finance, etc. to illustrate the applications of the methods described therein"--
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