Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

An examination of a proposed DSM-IV pathological gambling hierarchy in a treatment seeking population: similarities with substance dependence and evidence for three classification systems

Toce-Gerstein et al. (Addiction 98:1661–1672, 2003) investigated the distribution of Diagnostic and Statistical Manual for Mental Disorders, 4th edition (DSM-IV) pathological gambling criteria endorsement in a U.S. community sample for those people endorsing a least one of the DSM-IV criteria (n = 399). They proposed a hierarchy of gambling disorders where endorsement of 1–2 criteria were deemed ‘At-Risk’, 3–4 ‘Problem gamblers’, 5–7 ‘Low Pathological’, and 8–10 ‘High Pathological’ gamblers. This article examines these claims in a larger Australian treatment seeking population. Data from 4,349 clients attending specialist problem gambling services were assessed for meeting the ten DSM-IV pathological gambling criteria. Results found higher overall criteria endorsement frequencies, three components, a direct relationship between criteria endorsement and gambling severity, clustering of criteria similar to the Toce-Gerstein et al. taxonomy, high accuracy scores for numerical and criteria specific taxonomies, and also high accuracy scores for dichotomous pathological gambling diagnoses. These results suggest significant complexities in the frequencies of criteria reports and relationships between criteria.

Matrix constructions of centroid sets for classification systems

This article continues the investigation of matrix constructions motivated by their applications to the design of classification systems. Our main theorems strengthen and generalize previous results by describing all centroid sets for classification systems that can be generated as one-sided ideals with the largest weight in structural matrix semirings. Centroid sets are well known in data mining, where they are used for the design of centroid-based classification systems, as well as for the design of multiple classification systems combining several individual classifiers.

Mapping the knowledge covered by library classification systems

This study explores, in 3 steps, how the 3 main library classification systems, the Library of Congress Classification, the Dewey Decimal Classification, and the Universal Decimal Classification, cover human knowledge. First, we mapped the knowledge covered by the 3 systems. We used the 10 Pillars of Knowledge: Map of Human Knowledge, which comprises 10 pillars, as an evaluative model. We mapped all the subject-based classes and subclasses that are part of the first 2 levels of the 3 hierarchical structures. Then, we zoomed into each of the 10 pillars and analyzed how the three systems cover the 10 knowledge domains. Finally, we focused on the 3 library systems. Based on the way each one of them covers the 10 knowledge domains, it is evident that they failed to adequately and systematically present contemporary human knowledge. They are unsystematic and biased, and, at the top 2 levels of the hierarchical structures, they are incomplete.

Lake and reservoir classification systems /

Mode of access: Internet.

A summary of hazardous substance classification systems /

"An environmental protection publication in the solid waste management series (SW-171)."

Handbook for evaluating objective prison classification systems /

"June 1992."