Data Mining Algorithms in C++
Data Patterns and Algorithms for Modern Applications
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Discover hidden relationships among the variables in your data, and learn how to exploit these relationships. This book presents a collection of data-mining algorithms that are effective in a wide variety of prediction and classification applications. All algorithms include an intuitive explanation of operation, essential equations, references to more rigorous theory, and commented C++ source code.
Many of these techniques are recent developments, still not in widespread use. Others are standard algorithms given a fresh look. In every case, the focus is on practical applicability, with all code written in such a way that it can easily be included into any program. The Windows-based DATAMINE program lets you experiment with the techniques before incorporating them into your own work.
Use Monte-Carlo permutation tests to provide statistically sound assessments of relationships present in your data; Discover how combinatorially symmetric cross validation reveals whether your model has true power or has just learned noise by overfitting the data; Work with feature weighting as regularized energy-based learning to rank variables according to their predictive power when there is too little data for traditional methods; See how the eigenstructure of a dataset enables clustering of variables into groups that exist only within meaningful subspaces of the data; Plot regions of the variable space where there is disagreement between marginal and actual densities, or where contribution to mutual information is high.
by Timothy Masters
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, ...
Price: $32.58 | Publisher: Apress | Release: 2020
by David Natingga
Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical a...
Price: $39.99 | Publisher: Packt Publishing | Release: 2018
by Pawel Cichosz
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 pres...
Price: $70.55 | Publisher: Wiley | Release: 2015
by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser
Based on the authors' market leading data structures books in Java and C++, this textbook offers a comprehensive, definitive introduction to data structures in Python by respected authors. Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed to pr...
Price: $109.39 | Publisher: Wiley | Release: 2013
by Timothy Masters
Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting. This book presents many important techniques for building powerful,...
Price: $58.22 | Publisher: Apress | Release: 2018
by Luciano Manelli
Study elementary and complex algorithms with clear examples and implementations in C. This book introduces data types (simple and structured) and algorithms with graphical and textual explanations. In the next sections, you'll cover simple and complex standard algorithms with their flowcharts: everything is integrated with explanations an...
Price: $26.73 | Publisher: Apress | Release: 2020
by Amarpreet Singh Bassan, Debarchan Sarkar
Whether you are new to data mining or are a seasoned expert, this book will provide you with the skills you need to successfully create, customize, and work with Microsoft Data Mining Suite. Starting with the basics, this book will cover how to clean the data, design the problem, and choose a data mining model that will give you the most ...
Price: $29.99 | Publisher: Packt Publishing | Release: 2014
by Foster Provost, Tom Fawcett
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you und...
Price: $28.70 | Publisher: O'Reilly Media | Release: 2013