Introducing the Book

Polkowski, Lech; Tsumoto, Shusaku; Lin, Tsau Young

doi:10.1007/978-3-7908-1883-3_1

Cited by 67 publications

(44 citation statements)

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“…This section briefs on the basic notions of rough sets that is used in this paper and the detailed definitions can be referred to some related papers [1,3,10,12].…”

Section: Preliminariesmentioning

confidence: 99%

“…Rough set theory is a new mathematical approach to imperfect knowledge [10,12]. The principle notion of Rough Sets is that lowering the principle in data representation makes it possible to uncover patterns in the data, which may otherwise be obscured by too many details.…”

Section: A Rough Sets Theorymentioning

confidence: 99%

“…In other words, the essence of the information remains intact, and superfluous attributes are removed. Reducts have nicely characterized in [12] by discernibility matrices and discernibility functions.…”

Section: A Rough Sets Theorymentioning

confidence: 99%

“…Rough Sets [10]is used in the pre-processing stage in this paper that give the ability for dealing with inconsistency and noise reduction on the handwritten characters. This comes from the fact that Rough Sets can handle the missing feature value and inconsistency on the pattern [10,12]. Moreover, rough sets are able to get the most essential part of the knowledge with minimum number of features based on its concept of reduct.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid of Rough Neural Networks for Arabic/Farsi Handwriting Recognition

Radwan¹

2013

IJARAI

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Abstract-Handwritten character recognition is one of the focused areas of research in the field of Pattern Recognition. In this paper, a hybrid model of rough neural network has been developed for recognizing isolated Arabic/Farsi digital characters. It solves the neural network problems; proneness to overfitting, and the empirical nature of model development using rough sets and the dissimilarity analysis. Moreover the perturbation in the input data is violated using rough neuron. This paper describes an evolutionary rough neural network based technique to recognize Arabic/Farsi isolated handwritten digital characters. This method involves hierarchical feature extraction, data clustering and classification. In contrast with conventional neural network, a comparative study is appeared. Also, the details and limitations are discussed.

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“…This section briefs on the basic notions of rough sets that is used in this paper and the detailed definitions can be referred to some related papers [1,3,10,12].…”

Section: Preliminariesmentioning

confidence: 99%

Section: A Rough Sets Theorymentioning

confidence: 99%

Section: A Rough Sets Theorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hybrid of Rough Neural Networks for Arabic/Farsi Handwriting Recognition

Radwan¹

2013

IJARAI

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“…The theory of rough sets, proposed by Pawlak [28], has recently been used to analyze data sets for such a purpose. This theory is an extension of classical set theory for the study of systems characterized by insufficient and incomplete information, and has been demonstrated to be useful in fields such as pattern recognition, machine learning, and automated knowledge acquisition [14,27,[30][31][32]46,48]. Rough-set data analysis uses only internal knowledge, avoids external parameters, and does not rely on prior model assumptions such as probabilistic distribution in statistical methods, membership function in fuzzy sets theory, and basic probability assignment in Dempster-Shafer theory of evidence [7,33].…”

Section: Introductionmentioning

confidence: 99%

A Rough Set Approach for the Discovery of Classification Rules in Interval-Valued Information Systems

Leung

Fischer

et al. 2008

SSRN Journal

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A novel rough set approach is proposed in this paper to discover classification rules through a process of knowledge induction which selects optimal decision rules with a minimal set of features necessary and sufficient for classification of real-valued data. A rough set knowledge discovery framework is formulated for the analysis of interval-valued information systems converted from real-valued raw decision tables.The optimal feature selection method for information systems with interval-valued features obtains all classification rules hidden in a system through a knowledge induction process. Numerical examples are employed to substantiate the conceptual arguments.

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Data Mining in Medicine

Lavrač¹,

Zupan²

Data Mining and Knowledge Discovery Handbook

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Keywords:Extensive amounts of data stored in medical databases require the development of specialized tools for accessing the data, data analysis, knowledge discovery, and effective use of stored knowledge and data. This chapter focuses on Data Mining methods and tools for knowledge discovery. The chapter sketches the selected Data Mining techniques, and illustrates their applicability to medical diagnostic and prognostic problems.

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Introducing the Book

Cited by 67 publications

References 0 publications

Hybrid of Rough Neural Networks for Arabic/Farsi Handwriting Recognition

Hybrid of Rough Neural Networks for Arabic/Farsi Handwriting Recognition

A Rough Set Approach for the Discovery of Classification Rules in Interval-Valued Information Systems

Data Mining in Medicine

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