Data Mining: High-impact Strategies Review
Data Mining: High-impact Strategies Feature
Data mining (the analysis step of the Knowledge Discovery in Databases process, or Kdd), a relatively young and interdisciplinary field of computer science, is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management.
With recent technical advances in processing power, storage capacity, and inter-connectivity of computer technology, data mining is seen as an increasingly important tool by modern business to transform unprecedented quantities of digital data into business intelligence giving an informational advantage. It is currently used in a wide range of profiling practices, such as marketing, surveillance, fraud detection, and scientific discovery. The growing consensus that data mining can bring real value has led to an explosion in demand for novel data mining technologies.
This book is your ultimate resource for Data Mining. Here you will find the most up-to-date information, analysis, background and everything you need to know.
In easy to read chapters, with extensive references and links to get you to know all there is to know about Data Mining right away, covering: Data mining, Able Danger, Accuracy paradox, Affinity analysis, Alpha algorithm, Anomaly detection, Apatar, Apriori algorithm, Association rule learning, Automatic distillation of structure, Ball tree, Biclustering, Big data, Biomedical text mining, Business analytics, Canape, Cluster analysis, Clustering high-dimensional data, Co-occurrence networks, Concept drift, Concept mining, Consensus clustering, Correlation clustering, Cross Industry Standard Process for Data Mining, Cyber spying, Data Applied, Data classification (business intelligence), Data dredging, Data fusion, Data mining agent, Data Mining and Knowledge Discovery,
