A Tuned Stacking Algorithm to Detect Skin Cancer Using Multi-classification Algorithms-Reference-Cited by-同舟云学术

A Tuned Stacking Algorithm to Detect Skin Cancer Using Multi-classification Algorithms

Published:2023 Issue: Volume: Page:83-93
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Deva Rajashekar,Narsimha G.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-9989-5_8

Reference6 articles.

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2. Putatunda S (2020) A hybrid deep learning approach for diagnosis of the erythemato-squamous disease. In: 2020 IEEE international conference on electronics, computing and communication technologies (CONECCT). (2020, July). https://doi.org/10.1109/conecct50063.2020.9198447

3. Sivasubramanian S, Jacob SG (2020) An automated ontology learning for benchmarking classifier models through gain-based relative-non-redundant feature selection: a case-study with erythemato-squamous disease. Int J Bus Intell Data Min 16(3):261. https://doi.org/10.1504/ijbidm.2020.106132

4. Özçift A, Gülten A (2018) Genetic algorithm wrapped Bayesian network feature selection applied to differential diagnosis of erythemato-squamous diseases. Digit Signal Process 23(1):230–237. https://doi.org/10.1016/j.dsp.2012.07.008

5. Basu A, Roy SS, Abraham A (2015) A novel diagnostic approach based on support vector machine with linear kernel for classifying the erythemato-squamous disease. In: 2015 international conference on computing communication control and automation, pp 343–347. https://doi.org/10.1109/ICCUBEA.2015.72