Modern Data Mining Algorithms in C++ and CUDA C

Cheaper in another edition — £43.99 at Springer Nature Link Shop Modern Data Mining Algorithms in C++ and CUDA C · See that edition →

Discover a variety of data-mining algorithms that are useful for selecting small sets of important features from among unwieldy masses of candidates, or extracting useful features from measured variables. As a serious data miner you will often be faced with thousands of candidate features for your prediction or classification application, with most of the features being of little or no value. You’ll know that many of these features may be useful only in combination with certain other features while being practically worthless alone or in combination with most others. Some features may have enormous predictive power, but only within a small, specialized area of the feature space. The problems that plague modern data miners are endless. This book helps you solve this problem by presenting modern feature selection techniques and the code to implement them. Some of these techniques are: Forward selection component analysis Local feature selection Linking features and a target with a hidden Markov model Improvements on traditional stepwise selection Nominal-to-ordinal conversion All algorithms are intuitively justified and supported by the relevant equations and explanatory material.…

The cheapest new copy of Modern Data Mining Algorithms in C++ and CUDA C is £54.99 at Springer Nature Link Shop. Prices checked 8 Nov 2026

Other editions

More by Timothy Masters

More by Timothy Masters