RI algorithms normally based on PRISM suffer from a few drawbacks mainly related to rule pruning and rule-sharing items (attribute values) in the training data instances. In response to the above two issues, a new dynamic rule induction (DRI) method is proposed. Whenever a rule is produced ...
Vijay Kotu, Bala Deshpande PhD, in Predictive Analytics and Data Mining, 2015 4.2 Rule Induction Rule induction is a data mining process of deducing if-then rules from a data set. These symbolic decision rules explain an inherent relationship between the attributes and class labels in the data...
Rule induction provides a powerful classification approach that can be easily understood by the general audience. Apart from its use in Predictive Analytics by classification of unknown data, rule induction is also used to describe the patterns in the data. The description is in the form of ...
A novel predictive analysis approach for forecasting and classifying surface water data using AWQI standards and machine learning-based rule induction. Earth Sci Inform 18, 130 (2025). https://doi.org/10.1007/s12145-024-01558-2 Download citation Received22 July 2024 Accepted19 October 2024 ...
Rule-based models are often used for data analysis as they combine interpretability with predictive power. We present RuleKit 2, a versatile tool for rule learning. Based on a sequential covering induction algorithm, it is suitable for classification, regression, and survival problems. The presence...
Rule Induction with Extension Matrices Presents a heuristic, attribute-based, noise-tolerant data mining program, HCV (Version 2.0) based on the newly-developed extension matrix approach. Outlin... X Wu - 《Journal of the American Society for Information Science & Technology》 被引量: 22发表: ...
first makes asurveyon previous work in the area of contextual smartphone data analytics and then presents a discussion ofchallengesandfuture directionsfor effectively learning context-aware rules from smartphone data, in order to build rule-based automated and intelligent systems....
first makes asurveyon previous work in the area of contextual smartphone data analytics and then presents a discussion ofchallengesandfuture directionsfor effectively learning context-aware rules from smartphone data, in order to build rule-based automated and intelligent systems....
Modern monitoring tools rely on AI-empowered data analytics for detection, root cause analysis, and rapid resolution of performance degradation. However, the successful adoption of AI solutions is anchored on trust. System administrators will not unthinkingly follow the recommendations without s...
DataAnalyticsFuzzyUnorderedRuleInductionSimilaritymeasureThe need of similarity measures in life science is ever paramount given the modern biotechnology in producing and storing biomedical datasets in large amounts. This paper presents a novel scheme in measuring similarity of two datasets by prediction ...