A comparison of learning classifier systems' rule compaction algorithms for knowledge visualization
Learning Classifier Systems (LCSs) are a paradigm of rule-based evolutionary computation
(EC). LCSs excel in data-mining tasks regarding hel** humans to understand the …
(EC). LCSs excel in data-mining tasks regarding hel** humans to understand the …
[PDF][PDF] A hybrid deep learning based assist system for detection and classification of breast cancer from mammogram images.
The most common cancer disease among all women is breast cancer. This type of disease
is caused due to genetic mutation of ageing and lack of awareness. The tumour that …
is caused due to genetic mutation of ageing and lack of awareness. The tumour that …
[PDF][PDF] Rapid rule compaction strategies for global knowledge discovery in a supervised learning classifier system
Michigan-style learning classifier systems have availed themselves as a promising modeling
and data mining strategy for bioinformaticists seeking to connect predictive variables with …
and data mining strategy for bioinformaticists seeking to connect predictive variables with …
A comparison of rule compaction algorithms for michigan style learning classifier systems
Learning Classifier Systems (LCSs) excel in data mining tasks, eg an LCS optimal model
contains patterns that can precisely reveal how features identify classes for the explored …
contains patterns that can precisely reveal how features identify classes for the explored …
Learning Classifier Systems for Understanding Patterns in Data
Y Liu - 2021 - openaccess.wgtn.ac.nz
In the field of data-mining, symbolic techniques have produced optimal solutions, which are
expected to contain informative patterns. Visualizing these patterns can improve the …
expected to contain informative patterns. Visualizing these patterns can improve the …
Towards Digital Cancer Genetic Counseling
L Abujamous, A Tbakhi, M Odeh… - … on Cancer Care …, 2018 - ieeexplore.ieee.org
Early cancer diagnoses, combined with treatment, enhance survival and cure rates. In
Jordan, more than 20% of breast cancer patients present with advance stage disease …
Jordan, more than 20% of breast cancer patients present with advance stage disease …
[PDF][PDF] Smart doctor: Performance of supervised ART-I artificial neural network for breast cancer diagnoses
KR AL-Rawi, SK AL-Rawi - Iraqi Journal of Science, 2020 - iasj.net
Abstract Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance
of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural …
of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural …
Towards a process-based and service-oriented intelligent framework for Ig/TCR clonality testing in suspected lymphoproliferative neoplasms
Cancer care centers aim at automating the carried out procedures in their labs in order to
reduce staff effort and increase test accuracy. This has motivated the researchers …
reduce staff effort and increase test accuracy. This has motivated the researchers …
[PDF][PDF] An efficient spiking neural network approach based on spike response model for breast cancer diagnostic.
A Ourdighi, A Benyettou - Int. Arab J. Inf. Technol., 2016 - ccis2k.org
This study investigates the efficiency of the one-layered Spiking Neural Network (SNN) on
the enhancing of the breast cancer diagnostic results. The proposed network is based on …
the enhancing of the breast cancer diagnostic results. The proposed network is based on …
An Online Rule Set Compaction Strategy for the sUpervised Classifier System UCS
Abstract Learning Classifier Systems (LCS) are an adaptive rule based class of algorithms
driven by evolutionary mechanisms combined with machine learning. The goal of LCS is to …
driven by evolutionary mechanisms combined with machine learning. The goal of LCS is to …