Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Supoj Hengpraprohm"'
Autor:
Supoj Hengpraprohm, Suwimol Jungjit
Publikováno v:
Inteligencia Artificial, Vol 23, Iss 65 (2020)
For breast cancer data classification, we propose an ensemble filter feature selection approach named ‘EnSNR’. Entropy and SNR evaluation functions are used to find the features (genes) for the EnSNR subset. A Genetic Algorithm (GA) generates the
Externí odkaz:
https://doaj.org/article/1554d84cadb34475abb91b108a952860
Publikováno v:
International journal of health sciences. :2997-3006
This research aimed to develop the Artificial Intelligence (AI) indicator for elementary students by synthesizing the components of artificial intelligence learning for elementary students which is designed to be aware of the issue of mental health o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7083d8b89e8b93e9d5ae31304d50e50b
https://doi.org/10.53730/ijhs.v6ns8.12733
https://doi.org/10.53730/ijhs.v6ns8.12733
Publikováno v:
International journal of health sciences. :12239-12249
The article is a documentary research. The results were brought for assessment and trial, with the objectives to synthesize AI learning components for elementary students and to create the prototype AI learning modules for elementary students. The re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2565d5a8a750608f5866789b67e052a9
https://doi.org/10.53730/ijhs.v6ns4.11859
https://doi.org/10.53730/ijhs.v6ns4.11859
Publikováno v:
2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dadc80938989894416e6e36c3a392d29
https://doi.org/10.1109/jcsse54890.2022.9836306
https://doi.org/10.1109/jcsse54890.2022.9836306
Publikováno v:
Advanced Science Letters. 24:1330-1333
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8388e7ae0aca3707783f5b7d5b49fc72
https://doi.org/10.1166/asl.2018.10743
https://doi.org/10.1166/asl.2018.10743
Publikováno v:
Advanced Science Letters. 24:1348-1351
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3f9fc50dad749812e8466367c13cfb0
https://doi.org/10.1166/asl.2018.10747
https://doi.org/10.1166/asl.2018.10747
Autor:
Supoj Hengpraprohm
Publikováno v:
International Journal of Signal Processing Systems. 1:29-33
This work presents the method to classify the gene expression cancer data -Microarray data. The proposed method combines two techniques: classification and feature selection. The classification technique used in this work is Genetic Algorithm (GA) an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c8326ed595e9fd12af26dc3d21579608
https://doi.org/10.12720/ijsps.1.1.29-33
https://doi.org/10.12720/ijsps.1.1.29-33
Publikováno v:
2010 International Conference on Intelligent Computing and Cognitive Informatics.
This work presents an algorithm for generating the GA-based (Genetic Algorithm) classifier for microarray data classification. The microarray dataset comprises of a small number of samples with very high features. In order to construct the GA-based c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e27ed9e31745ccdbfd393c15d1b6adb
https://doi.org/10.1109/icicci.2010.62
https://doi.org/10.1109/icicci.2010.62
Publikováno v:
2008 3rd International Conference on Innovative Computing Information and Control.
This paper presents a method for building an ensemble of classifiers for cancer microarray data. The proposed method exploits the advantage of a clustering technique, namely K-means clustering, combined with a feature selection technique, namely SNR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ec0c2c78f1ffca78117a11439782d09
https://doi.org/10.1109/icicic.2008.35
https://doi.org/10.1109/icicic.2008.35
Publikováno v:
FBIT
This paper presents a method for selecting informative features using K-Means clustering and SNR ranking. The performance of the proposed method was tested on cancer classification problems. Genetic Programming is employed as a classifier. The experi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e3c57fe6cca19663f0d7aafd8e09be2
https://doi.org/10.1109/fbit.2007.84
https://doi.org/10.1109/fbit.2007.84