Titlebook: Data Mining and Knowledge Discovery via Logic-Based Methods; Theory, Algorithms, Evangelos Triantaphyllou Book 2010 Springer Science+Busin

愚蠢地活

书目名称Data Mining and Knowledge Discovery via Logic-Based Methods影响因子(影响力)




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods影响因子(影响力)学科排名




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods网络公开度




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods网络公开度学科排名




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods被引频次




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods被引频次学科排名




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods年度引用




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods年度引用学科排名




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods读者反馈




书目名称Data Mining and Knowledge Discovery via Logic-Based Methods读者反馈学科排名

与野兽博斗者

A Revised Branch-and-Bound Approach for Inferring a Boolean Function from Examplesng examples. This algorithm is an extension of the B&B algorithm described in the previous chapter. Now the states of the search space are described by using more information and this seems to be critical in leading to good search results faster. This chapter is based on the developments first prese

闷热

Some Fast Heuristics for Inferring a Boolean Function from Examplesor inferring a Boolean function in the form of a compact (i.e., with as few clauses as possible) CNF or DNF expression from two collections of disjoint examples. As was described in Chapters 2 and 3, the B&B approaches may take a long time to run (actually, they are of exponential time complexity).

forestry

Kinetic

An Incremental Learning Algorithm for Inferring Boolean Functionsheoracle for classification and use that information to improve the understanding of the system under consideration. When the new example would unveil the need for an update, one had to use all the existing training examples, plus the newly classified example, to infer a new (and hopefully more accu

有恶意

The Reliability Issue in Data Mining: The Case of Computer-Aided Breast Cancer Diagnosisst data. This accuracy can be a general description of how well the extracted model classifies test data. Some studies split thisaccuracy rate into two rates: thefalse-positive andfalse-negative rates. This distinction might be more appropriate for most real-life applications. For instance, it is on

有恶意

Data Mining and Knowledge Discovery by Means of Monotone Boolean Functionsly inferred if all possible binary examples (states) in the space of the attributes are used for training. Thus, one may never be 100% certain about the validity of the inferred knowledge when the number of training examples is less than 2.. The situation is different, however, if one deals with the

不能仁慈

Some Application Issues of Monotone Boolean Functionsuracy make the search for this property in data and its consecutive algorithmic exploitation, to be of high potential in data mining and knowledge discovery applications. The following developments are based on the work described in [ Kovalerchuk,Vityaev, andTriantaphyllou, 1996] and [ Kovalerchuk,T

slipped-disk

overreach