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Integrating Classification and Association Rule Mining
TLDR
The integration is done by focusing on mining a special subset of association rules, called class association rules (CARs), and shows that the classifier built this way is more accurate than that produced by the state-of-the-art classification system C4.5.
Mining association rules with multiple minimum supports
TLDR
This paper proposes a novel technique that allows the user to specify multiple minimum supports to reflect the natures of the items and their varied frequencies in the database and shows that the technique is very effective.
Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes
TLDR
In this evaluation of retinal images from multiethnic cohorts of patients with diabetes, the DLS had high sensitivity and specificity for identifying diabetic retinopathy and related eye diseases.
XClust: clustering XML schemas for effective integration
TLDR
XClust is introduced, a novel integration strategy that involves the clustering of DTDs that are similar in structure and semantics and a matching algorithm based on the semantics, immediate descendents and leaf-context similarity of D TD elements is developed.
Mining relationships among interval-based events for classification
TLDR
This paper augments the hierarchical representation of interval-based events with additional information to achieve a lossless representation, and builds an interval- based classifier called IEClassifier to differentiate closely related classes.
Using General Impressions to Analyze Discovered Classification Rules
TLDR
This paper proposes a technique that analyzes the discovered rules against a specific type of existing knowledge, which is called general impressions, to help the user identify interesting rules.
Pruning and summarizing the discovered associations
TLDR
The technique first prunes the discovered associations to remove those insignificant associations, and then finds a special subset of the unpruned associations to form a summary of the discovered association rules, which are then called the direction setting rules.
A prime number labeling scheme for dynamic ordered XML trees
TLDR
This work proposes a new labeling scheme that take advantage of the unique property of prime numbers to meet the need for efficient support to order-sensitive queries and updates of XML queries.
DESIGN OF MUTANT OPERATORS FOR THE C PROGRAMMING LANGUAGE
TLDR
This report describes the mutant operators designed for the proposed ANSI C programming language and intends this report to serve as a manual for the C mutant operators for researchers in software testing.
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