Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.They will hopefully encourage at least some readers to study readily available tutorials and provide useful starting points for such self-study. ... In some examples tiny and totally unrealistic datasets are used to make it possible to manually verify the results. ... On several occasions, however, publicly available real datasets are used, available in CRAN packages and ... Since the booka#39;s chapters were created over an extended period of time, there are some noticeable inconsistenciesanbsp;...
|Title||:||Data Mining Algorithms|
|Publisher||:||John Wiley & Sons - 2014-11-17|