Towards industrial revolution 5.0 and explainable artificial intelligence: Challenges and opportunities
I Taj, N Zaman - International Journal of Computing and Digital …, 2022 - journal.uob.edu.bh
Technological growth is changing our everyday living, making it smarter and more
convenient day by day; Smart society 5.0, Healthcare 5.0, Agriculture 5.0 are only a few …
convenient day by day; Smart society 5.0, Healthcare 5.0, Agriculture 5.0 are only a few …
Black-box vs. white-box: Understanding their advantages and weaknesses from a practical point of view
O Loyola-Gonzalez - IEEE access, 2019 - ieeexplore.ieee.org
Nowadays, in the international scientific community of machine learning, there exists an
enormous discussion about the use of black-box models or explainable models; especially …
enormous discussion about the use of black-box models or explainable models; especially …
FPGA-based implementation of classification techniques: A survey
Recently, a number of classification techniques have been introduced. However, processing
large dataset in a reasonable time has become a major challenge. This made classification …
large dataset in a reasonable time has become a major challenge. This made classification …
Decision tree underfitting in mining of gene expression data. An evolutionary multi-test tree approach
M Czajkowski, M Kretowski - Expert Systems with Applications, 2019 - Elsevier
The problem of underfitting and overfitting in machine learning is often associated with a
bias-variance trade-off. The underfitting most clearly manifests in the tree-based inducers …
bias-variance trade-off. The underfitting most clearly manifests in the tree-based inducers …
Synthetic minority oversampling in addressing imbalanced sarcasm detection in social media
A Banerjee, M Bhattacharjee, K Ghosh… - Multimedia Tools and …, 2020 - Springer
Recent developments in sarcasm detection have been emerged as extremely successful
tools in Social media opinion mining. With the advent of machine learning tools, accurate …
tools in Social media opinion mining. With the advent of machine learning tools, accurate …
Lung cancer diagnosis based on weighted convolutional neural network using gene data expression
Lung cancer is thought to be a genetic disease with a variety of unknown origins.
Globocan2020 report tells in 2020 new cancer cases identified was 19.3 million and nearly …
Globocan2020 report tells in 2020 new cancer cases identified was 19.3 million and nearly …
A comparative study of nature-inspired metaheuristic algorithms using a three-phase hybrid approach for gene selection and classification in high-dimensional cancer …
Identification of informative genes is essential for the disease and cancer studies.
Metaheuristic algorithms have been widely used for this purpose. However, their …
Metaheuristic algorithms have been widely used for this purpose. However, their …
How effective is the salp swarm algorithm in data classification
In this paper, the Salp Swam Algorithm (SSA) is deployed in training the Multilayer
Perceptron (MLP) for the task of data classification. The UCI machine learning repository …
Perceptron (MLP) for the task of data classification. The UCI machine learning repository …
Application of neutrosophic logic to evaluate correlation between prostate cancer mortality and dietary fat assumption
M Aslam, M Albassam - Symmetry, 2019 - mdpi.com
This paper presents an epidemiological study on the dietary fat that causes prostate cancer
in an uncertainty environment. To study this relationship under the indeterminate …
in an uncertainty environment. To study this relationship under the indeterminate …
Detection of colon cancer based on microarray dataset using machine learning as a feature selection and classification techniques
Microarray data is an increasingly important tool for providing information on gene
expression for analysis and interpretation. Researchers attempt to utilize the smallest …
expression for analysis and interpretation. Researchers attempt to utilize the smallest …