Data Mining: A Heuristic Approach

Read Online or Download Data Mining: A Heuristic Approach PDF

Similar data mining books

Machine Learning: The Art and Science of Algorithms that Make Sense of Data

As probably the most entire computer studying texts round, this e-book does justice to the field's extraordinary richness, yet with no wasting sight of the unifying ideas. Peter Flach's transparent, example-based method starts off through discussing how a junk mail filter out works, which provides a right away advent to computing device studying in motion, with at the very least technical fuss.

Fuzzy logic, identification, and predictive control

The complexity and sensitivity of contemporary commercial strategies and platforms more and more require adaptable complicated keep watch over protocols. those controllers need to be capable of take care of conditions not easy ôjudgementö instead of easy ôyes/noö, ôon/offö responses, situations the place an obscure linguistic description is usually extra appropriate than a cut-and-dried numerical one.

Data Clustering in C++: An Object-Oriented Approach

Information clustering is a hugely interdisciplinary box, the objective of that's to divide a suite of gadgets into homogeneous teams such that items within the related crew are related and gadgets in numerous teams are rather designated. millions of theoretical papers and a couple of books on information clustering were released over the last 50 years.

Fifty Years of Fuzzy Logic and its Applications

Entire and well timed document on fuzzy good judgment and its applications
Analyzes the paradigm shift in uncertainty administration upon the creation of fuzzy logic
Edited and written by means of best scientists in either theoretical and utilized fuzzy logic

This e-book offers a complete document at the evolution of Fuzzy good judgment due to the fact that its formula in Lotfi Zadeh’s seminal paper on “fuzzy sets,” released in 1965. furthermore, it encompasses a stimulating sampling from the wide box of study and improvement encouraged by means of Zadeh’s paper. The chapters, written through pioneers and well-known students within the box, convey how fuzzy units were effectively utilized to man made intelligence, regulate conception, inference, and reasoning. The e-book additionally studies on theoretical matters; gains fresh functions of Fuzzy common sense within the fields of neural networks, clustering, info mining and software program trying out; and highlights a big paradigm shift attributable to Fuzzy good judgment within the quarter of uncertainty administration. Conceived through the editors as an instructional social gathering of the fifty years’ anniversary of the 1965 paper, this paintings is a must have for college students and researchers prepared to get an inspiring photograph of the possibilities, obstacles, achievements and accomplishments of Fuzzy Logic-based systems.

Topics
Computational Intelligence
Data Mining and data Discovery
Control
Artificial Intelligence (incl. Robotics)

Additional info for Data Mining: A Heuristic Approach

Example text

36 Hsu Subset Selection and Partitioning Attribute subset selection, also called feature subset selection, is the task of focusing a learning algorithm’s attention on some subset of the given input attributes, while ignoring the rest (Kohavi & John, 1997). In this research, subset selection is adapted to the systematic decomposition of learning problems over heterogeneous time series. Instead of focusing a single algorithm on a single subset, the set of all input attributes is partitioned, and a specialized algorithm is focused on each subset.

Larsson, S. (1999). org. & Smyth, P. (2001). Principles of data mining. Cambridge, MA: MIT Press. Heckerman, D. (1997). Bayesian networks for data mining. Data Mining and Knowledge Discovery 1, 79-119. Jaynes, E. T. (2003). Probability theory: The logic of science. Cambridge University Press, ISBN: 0521592712. Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. , & Tomkins, A. (2001). Recommendation systems: A probabilistic analysis.

This chapter presents an integrated, multi-strategy system for decomposition of time series classifier learning tasks. A typical application for such a system is learning to predict and classify hazardous and potentially catastrophic conditions. This prediction task is also known as crisis monitoring, a form of pattern recognition that is useful in decision support or recommender systems (Resnick & Varian, 1997) for many time-critical applications. Examples of crisis monitoring problems in the industrial, military, agricultural, and environmental sciences are numerous.

Download PDF sample

Rated 4.83 of 5 – based on 33 votes