Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science) Book PDF, ePub eBook

Join our eBook service for unlimited books & audiobooks. Get a free 7 day subscription! ↓↓↓↓↓


Book Descriptions:
As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com­ puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys­ tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science) by Huan Liu, Hiroshi Motoda

From reader reviews:

Joanne Hall:

As people who live in the actual modest era should be update about what going on or information even knowledge to make these keep up with the era which can be always change and move ahead. Some of you maybe will certainly update themselves by examining books. It is a good choice in your case but the problems coming to you actually is you don't know which you should start with. This Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science) is our recommendation so you keep up with the world. Why, because book serves what you want and want in this era.

Frances Barrett:

Hey guys, do you wishes to finds a new book to learn? May be the book with the subject Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science) suitable to you? Often the book was written by renowned writer in this era. The book untitled Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science)is the main of several books that will everyone read now. This kind of book was inspired a number of people in the world. When you read this guide you will enter the new dimensions that you ever know ahead of. The author explained their concept in the simple way, so all of people can easily to recognise the core of this book. This book will give you a wide range of information about this world now. In order to see the represented of the world with this book.

Helen Jackson:

This Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science) is great reserve for you because the content that is full of information for you who all always deal with world and possess to make decision every minute. This kind of book reveal it info accurately using great coordinate word or we can claim no rambling sentences inside. So if you are read the item hurriedly you can have whole information in it. Doesn't mean it only gives you straight forward sentences but tricky core information with attractive delivering sentences. Having Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science) in your hand like getting the world in your arm, information in it is not ridiculous one particular. We can say that no e-book that offer you world with ten or fifteen second right but this e-book already do that. So , this is certainly good reading book. Hi Mr. and Mrs. stressful do you still doubt this?

Michael Kautz:

You are able to spend your free time to read this book this book. This Feature Selection for Knowledge Discovery and Data Mining (The Springer International Series in Engineering and Computer Science) is simple bringing you can read it in the recreation area, in the beach, train in addition to soon. If you did not possess much space to bring typically the printed book, you can buy the actual e-book. It is make you simpler to read it. You can save the book in your smart phone. Consequently there are a lot of benefits that you will get when one buys this book.