The achieved outcomes regarding the statistical metrics of the designed classifiers.

The achieved outcomes regarding the statistical metrics of the designed classifiers.

<p>The achieved outcomes regarding the statistical metrics of the designed classifiers.</p>

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Bibliographic Details
Main Author:	Hamed Khodadadi (21446172) (author)
Other Authors:	Shima Nazem (21446175) (author)
Published:	2025
Subjects:	Biotechnology Cancer Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified significant health issue optimize feature selection measures temperature variations including lyapunov exponent improving patient outcomes fitting neural network analyzing breast thermograms 65 %, emphasizes svm ), k pat net ), fit net ), improving cancer detection extracts relevant features kse ), cd ), early detection texture features complexity features superior performance study proposes sinai entropy reduce redundancy proposed method proposed approach promising approach occurrence matrix nsga iii novel method nearest neighbors method utilized level co integrating texture high rates fold cross early diagnosis correlation dimension comprehensive analysis chaotic indices cancerous tissues aided diagnosis achieved accuracy
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Summary:	<p>The achieved outcomes regarding the statistical metrics of the designed classifiers.</p>

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