Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features …
From the Foreword:"While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in …
Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the …
Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, …
Unstructured Mining Approaches to Solve Complex Scientific ProblemsAs the volume of scientific data and literature increases exponentially, scientists need more powerful tools and …
Learn How to Properly Use the Latest Analytics Approaches in Your OrganizationComputational Business Analytics presents tools and techniques for descriptive, predictive, and …
Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has …
Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from …
Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly …
A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from …
