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Peculiarity Analysis for Classifications | IEEE Conference Publication
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Abstract: Peculiarity-oriented mining (POM) is a new data mining method consisting of peculiar data identification and peculiar data analysis.
Peculiarity-oriented mining (POM) is a new data mining method consisting of peculiar data identification and peculiar data analysis. Peculiarity factor (PF) ...
This provides a theoretical basis for some existing distance based anomaly detection techniques. More important, it also provides an effective method for ...
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... peculiarity analysis for classification problems. A novel algorithm called LPF-Bayes classifier and its kernelized implementation are presented, which have ...
Jul 1, 2010 · Peculiarity-oriented mining is a data mining method consisting of peculiar data identification and peculiar data analysis.
Peculiarity-oriented mining is a data mining method consisting of peculiar data identification and peculiar data analysis. Peculiarity factor and local ...
Dec 21, 2021 · The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features.
Nov 9, 2023 · Classification analysis is a data analytics technique that assigns labels or categories to data points based on their features or attributes.
May 6, 2023 · The goal of classification is to build a model that accurately predicts the class labels of new instances based on their features. There are two ...
Jun 4, 2023 · Classification analysis is a data analytics technique that can be used to predict customer churn. Data analytics professionals typically use ...