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Advanced Intelligent Discovery, EarlyView.This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
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An Overview of Data Mining Representation Techniques
2019 7th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), 2019Current data mining systems and techniques are used with the objective of finding future values for datasets, leaving aside what could be even more useful information, by not exploring deeper into the outputs of such techniques. This paper presents an overview of the major representation and visualization techniques available and usable to bring forth ...
Domingos Costa +2 more
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2023
When referring to a group of methodologies, algorithms, and tools used to draw significant patterns, connections, and insights from huge datasets, we are referring to data mining techniques. These methods are essential for finding concealed information and for developing sensible conclusions across a variety of fields.
Dr.I.Parvin Begum, D.Nasreen Banu
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When referring to a group of methodologies, algorithms, and tools used to draw significant patterns, connections, and insights from huge datasets, we are referring to data mining techniques. These methods are essential for finding concealed information and for developing sensible conclusions across a variety of fields.
Dr.I.Parvin Begum, D.Nasreen Banu
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Soft Techniques to Data Mining
1998This paper describes two soft techniques, GDT-NN and GDTRS, for mining if-then rules in databases with uncertainty and incompleteness. The techniques are based on a Generalization Distribution Table (GDT), in which the probabilistic relationships between concepts and instances over discrete domains are represented.
Ning Zhong 0001 +2 more
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Natural data mining techniques
Bull. EATCS, 2000Summary: All techniques showed in this paper are directly applicable to machine learning tasks in general, and to data mining problems in particular. As mentioned in Section 1, methods can be compared according to three criteria, efficiency; effectivity and interpretability of the outcomes.
Joost N. Kok, Walter A. Kosters
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Proceedings of the 1996 ACM SIGMOD international conference on Management of data - SIGMOD '96, 1996
Data mining, or knowledge discovery in databases, has been popularly recognized as an important research issue with broad applications. We provide a comprehensive survey, in database perspective, on the data mining techniques developed recently. Several major kinds of data mining methods, including generalization, characterization, classification ...
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Data mining, or knowledge discovery in databases, has been popularly recognized as an important research issue with broad applications. We provide a comprehensive survey, in database perspective, on the data mining techniques developed recently. Several major kinds of data mining methods, including generalization, characterization, classification ...
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Survey on data mining classification techniques
Proceedings of the International Conference & Workshop on Emerging Trends in Technology - ICWET '11, 2011Data volumes have increased noticeably in the few passed years and also expected to have consistent growth in coming years. Data mining is the most promising solution for dealing with such huge amount of data with little knowledge for its categorization as it helps in organizing data into sensible groupings.
N. Vandana Sawant +2 more
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Data Mining Techniques for Employee Evaluation
2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), 2020The article shows how complex the human resource field is, how much artificial intelligence can influence a field and how some companies already used artificial intelligence (AI) to improve their human resources (HR) capabilities. The paper’s main objective was to identify a way to evaluate whether the managers promote or offer benefits to employees in
Andreea Nedelcu +3 more
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Techniques of Cluster Algorithms in Data Mining
Data Mining and Knowledge Discovery, 2002An overview of cluster analysis techniques from a data mining point of view is given. This is done by a strict separation of the questions of various similarity and distance measures and related optimization criteria for clusterings from the methods to create and modify clusterings themselves.
Johannes Grabmeier, Andreas Rudolph
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