000			01313cam a22002058i 4500
020			_a9781032065366
020			_a9781032071596
082	0	0	_a006.32 _223 _bTSA
100	1		_aTsai, Kao-Tai,
245	1	0	_aMachine learning for knowledge discovery with R : _bmethodologies for modeling, inference and prediction / _cKao-Tai Tsai.
250			_aFirst edition.
260			_aBoca raton _bCRC Press _c2022
300			_axv, 244 pages
504			_aIncludes bibliographical references and index.
520			_a"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"--
650		0	_aData mining
650		0	_aMachine learning.
650		0	_aR (Computer program language)
942			_cBK
999			_c628965 _d628965