Principles of Data Mining (Adaptive Computation and Machine Learning) (Repost)

Description

The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

Disclaimer:
Contents of this page are indexed from the Internet. All actions are under your responsability. Email us to report illegal contents or external links and we'll remove them immediately.

Please check the description for download links if any or do a search to find alternative books.

Can't Download?
Please search mirrors if you can't find download links for "Principles of Data Mining (Adaptive Computation and Machine Learning) (Repost)" in "Description" and someone else may update the links. Check the comments when back to find any updates.

Search Mirrors
Maybe some mirror pages will be helpful, search this book at top of this page or click here to find more info.

1. Ebooks list page : 3648
2. Principles of Data Mining Adaptive Computation and Machine Learning
3. Principles of Data Mining (Adaptive Computation and Machine Learning) by David J. Hand
4. Principles of Data Mining (Adaptive Computation and Machine Learning) by David J. Hand
5. Principles of Data Mining (Adaptive Computation and Machine Learning)
6. Principles of Data Mining (Adaptive Computation and Machine Learning)
7. Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
8. Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 5th European Conferenc
9. Principles and Theory for Data Mining and Machine Learning
10. [share_ebook] Principles and Theory for Data Mining and Machine Learning
11. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
12. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
13. Introduction to Machine Learning (Adaptive Computation and Machine Learning)
14. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Repost)
15. Causation, Prediction, and Search, Second Edition (Adaptive Computation and Machine Learning)
16. Data Mining: Practical Machine Learning Tools and Techniques