Fee Download Data Mining With Decision Trees: Theory And Applications, by Lior Rokach
Nevertheless, reading guide Data Mining With Decision Trees: Theory And Applications, By Lior Rokach in this site will lead you not to bring the published book anywhere you go. Simply store the book in MMC or computer disk and they are readily available to read at any time. The prosperous air conditioner by reading this soft documents of the Data Mining With Decision Trees: Theory And Applications, By Lior Rokach can be introduced something brand-new practice. So currently, this is time to show if reading can improve your life or otherwise. Make Data Mining With Decision Trees: Theory And Applications, By Lior Rokach it undoubtedly work as well as get all benefits.
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach
Fee Download Data Mining With Decision Trees: Theory And Applications, by Lior Rokach
Excellent Data Mining With Decision Trees: Theory And Applications, By Lior Rokach book is always being the most effective friend for spending little time in your office, night time, bus, and anywhere. It will be an excellent way to simply look, open, and also read guide Data Mining With Decision Trees: Theory And Applications, By Lior Rokach while in that time. As known, encounter and also ability do not consistently included the much cash to obtain them. Reading this publication with the title Data Mining With Decision Trees: Theory And Applications, By Lior Rokach will certainly let you know more things.
Below, we have various book Data Mining With Decision Trees: Theory And Applications, By Lior Rokach and collections to check out. We likewise serve variant types and also kinds of guides to search. The fun publication, fiction, past history, unique, scientific research, and also various other sorts of e-books are readily available below. As this Data Mining With Decision Trees: Theory And Applications, By Lior Rokach, it ends up being one of the recommended e-book Data Mining With Decision Trees: Theory And Applications, By Lior Rokach collections that we have. This is why you are in the right site to see the fantastic publications to own.
It won't take even more time to obtain this Data Mining With Decision Trees: Theory And Applications, By Lior Rokach It will not take even more money to publish this book Data Mining With Decision Trees: Theory And Applications, By Lior Rokach Nowadays, individuals have actually been so smart to utilize the modern technology. Why don't you use your device or other gadget to conserve this downloaded soft documents book Data Mining With Decision Trees: Theory And Applications, By Lior Rokach Through this will certainly allow you to constantly be gone along with by this e-book Data Mining With Decision Trees: Theory And Applications, By Lior Rokach Certainly, it will be the ideal close friend if you read this e-book Data Mining With Decision Trees: Theory And Applications, By Lior Rokach up until completed.
Be the first to download this e-book now and obtain all reasons you require to read this Data Mining With Decision Trees: Theory And Applications, By Lior Rokach The e-book Data Mining With Decision Trees: Theory And Applications, By Lior Rokach is not simply for your obligations or necessity in your life. Publications will certainly always be a good friend in whenever you read. Now, let the others learn about this page. You could take the perks as well as discuss it likewise for your buddies and people around you. By in this manner, you could actually get the significance of this publication Data Mining With Decision Trees: Theory And Applications, By Lior Rokach profitably. What do you think of our concept below?
“. . . the book is a very useful and nice coverage of the field . . . It is highly recommendable for people who want to begin working in this field and need guidance to start into the large area of applying these methods.” Zentralblatt Math This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique. Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. The area is of great importance because it enables modeling and knowledge extraction from the abundance of data available. Both theoreticians and practitioners are continually seeking techniques to make the process more efficient, cost-effective and accurate. Decision trees, originally implemented in decision theory and statistics, are highly effective tools in other areas such as data mining, text mining, information extraction, machine learning, and pattern recognition. This book invites readers to explore the many benefits in data mining that decision trees offer: Self-explanatory and easy to follow when compacted Able to handle a variety of input data: nominal, numeric and textual Able to process datasets that may have errors or missing values High predictive performance for a relatively small computational effort Available in many data mining packages over a variety of platforms Useful for various tasks, such as classification, regression, clustering and feature selection
- Sales Rank: #8546731 in Books
- Published on: 2007-12-17
- Released on: 2007-12-17
- Original language: English
- Dimensions: 9.00" h x .60" w x 6.00" l,
- Binding: Paperback
- 262 pages
Most helpful customer reviews
5 of 5 people found the following review helpful.
Specialists should consider it, Practitioners should look elsewhere
By Keith McCormick
I will recommend this to one or two colleagues, but it will not be something I will recommend to clients.
The first thing you notice about this book is its very academic style. It has numbered paragraphs like 2.0, and 7.3.1.12. It been used a graduate text, presumably for mathematicians and computer scientists. I think it would be good for that purpose. It could work quite well for statisticians that are interested in the details of data mining algorithms. It is in a series in Machine Perception and Artificial Intelligence. Other titles include "Fundamentals of Robotics", and "Bridging the Gap Between Graph Edit Distance and Kernel Machines", so don't confuse this book with something like Data Mining Techniques, which is written for a general audience. It opens the 2nd chapter with (condensed): "A training set is a bag instance of a bag schema. A bag instance is a collection of tuples that may contain duplicates." The folks that I work with can instantly divide themselves into those that would consider a book like this, and those that wouldn't. It cites references in almost every sentence, which can be distracting to the casual reader, and eventually convinced me that I need to read the original authors like Breiman. Classification and Regression Trees
So having issued a warning, there is plenty to like. The authors have made a real attempt to cover everything - I found 1/3 that I knew, 1/3 that will be quite useful to me, and 1/3 that is too much detail for me. Chapter 3 "Evaluation of Classification Trees" will be great for statisticians that wondered how to judge the efficacy of a tree that was built without hypothesis testing. Also, I was very pleased to see a chapter on "Decision Forests", which is a discussion of "ensemble methods" - in other words combining a set of tree models.
I was hoping for something that would have a detailed chapter on each of the most common decision trees algorithms with briefer sections on the obscure ones. It has all this information, but in a way that I have to work pretty hard to get to it. If you want a quick overview of data mining (even if you think that trees are the method you are going to use), try Data Mining Techniques. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management If you want to know the details, but are content to learn the details only on the well known techniques (like CHAID and CART) then Larose is a good choice. Discovering Knowledge in Data: An Introduction to Data Mining
3 of 3 people found the following review helpful.
Survey of the literature, not a standalone work
By D. Wilson
The important thing to know about this book before purchasing is that it does not, on the whole, stand on its own. It covers a great number of topics relating to decision trees and their use, but the coverage is primarily as a survey of the literature rather than as usage examples or algorithmic details. Most of the book takes a very qualitative look at the topics; there are few if any quantitative results to be found within.
If you're looking for a collection of organized references to important papers on the topic of decision trees and you've access to the archives of the cited journals, then this book is useful as a jumping-off point to see how the various papers relate. If you're looking for a standalone book on the topic, look elsewhere.
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach PDF
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach EPub
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach Doc
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach iBooks
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach rtf
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach Mobipocket
Data Mining With Decision Trees: Theory And Applications, by Lior Rokach Kindle
Tidak ada komentar:
Posting Komentar