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Quantum-inspired attribute selection algorithms
Quantum Science and TechnologyAbstract In this study, we propose the use of quantum information gain (QIG) and fidelity as quantum splitting criteria to construct an efficient and balanced quantum decision tree. QIG is a circuit-based criterion in which angle embedding is used to construct a quantum state, which utilizes quantum mutual information to compute the ...
Diksha Sharma +2 more
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2012 International Conference on Radar, Communication and Computing (ICRCC), 2012
Data mining is a process of finding hidden information from databases storing historical data which are also known as data-warehouses. Classification being a very well-known data mining technique, groups similar data objects by establishing relationship between the objects under test and the pre-defined class labels obtained during training phase.
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Data mining is a process of finding hidden information from databases storing historical data which are also known as data-warehouses. Classification being a very well-known data mining technique, groups similar data objects by establishing relationship between the objects under test and the pre-defined class labels obtained during training phase.
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Efficient attribute selection technique for leukaemia prediction using microarray gene data
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2020D. Santhakumar, S. Logeswari
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The Selection of the Attributes
1971The problem of how to select an effective set of attributes for a PRD is generally considered the single most difficult problem in the design. The problem is frequently discussed in the literature (Levine 1969; Nagy 1969; Nelson and Levy; Fu et al. 1970; Henderson and Lainiotis 1970) and is the topic of September 1971 issue of the IEEE Transactions on ...
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Attribute Selection Based on Reduction of Numerical Attributes During Discretization
2017Some numerical attributes may be reduced during discretization. It happens when a discretized attribute has only one interval, i.e., the entire domain of a numerical attribute is mapped into a single interval. The problem is how such reduction of data sets affects the error rate measured by the C4.5 decision tree generation system using ten-fold cross ...
Jerzy W. Grzymała-Busse, Teresa Mroczek
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Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2019
Shivani Singh +3 more
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Shivani Singh +3 more
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Learning refined attribute-aligned network with attribute selection for person re-identification
Neurocomputing, 2020Yuxuan Shi +4 more
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A multi-scale information fusion-based multiple correlations for unsupervised attribute selection
Information FusionPengfei Zhang +5 more
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The Arabian journal for science and engineering, 2019
Priyanka Verma +2 more
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Priyanka Verma +2 more
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