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Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning
Cancer is a fatal disease caused by a combination of genetic diseases and a variety of
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
Development of different machine learning ensemble classifier for gully erosion susceptibility in Gandheswari Watershed of West Bengal, India
In various types of geo-environmental problems in the fringing area of Chhotanagpur
plateau in India, gully erosion is one of the vulnerable issue. In our current research, using …
plateau in India, gully erosion is one of the vulnerable issue. In our current research, using …
A cnn approach for corn leaves disease detection to support digital agricultural system
Correct, fast and early detection of corn leave diseases and their prevention and control at
the earlier stages is profitable. To improve the detection accuracy of corn leaf diseases, a …
the earlier stages is profitable. To improve the detection accuracy of corn leaf diseases, a …
[HTML][HTML] A Jaya algorithm based wrapper method for optimal feature selection in supervised classification
In recent years, Jaya optimization algorithm has been successfully applied in several
optimization problems. This paper presents a novel feature selection (FS) approach based …
optimization problems. This paper presents a novel feature selection (FS) approach based …
Feature selection using golden jackal optimization for software fault prediction
A program's bug, fault, or mistake that results in unintended results is known as a software
defect or fault. Software flaws are programming errors due to mistakes in the requirements …
defect or fault. Software flaws are programming errors due to mistakes in the requirements …
Enhancing software fault prediction through feature selection with spider wasp optimization algorithm
Software fault prediction (SFP) is a critical focus in software engineering, aiming to enhance
productivity and minimize costs by detecting faults early. Feature selection (FS) is pivotal in …
productivity and minimize costs by detecting faults early. Feature selection (FS) is pivotal in …
COVID-19 world vaccination progress using machine learning classification algorithms
Abstract In December 2019, SARS-CoV-2 caused coronavirus disease (COVID-19)
distributed to all countries, infecting thousands of people and causing deaths. COVID-19 …
distributed to all countries, infecting thousands of people and causing deaths. COVID-19 …
Optimal selection of features using artificial electric field algorithm for classification
The high-dimensional features in the data may affect the performance of the classification
model as all of them are not useful. The selection of relevant optimal features is a tedious …
model as all of them are not useful. The selection of relevant optimal features is a tedious …
[HTML][HTML] Biomedical data analysis using neuro-fuzzy model with post-feature reduction
Now-a-days, a large volume of biomedical data are continuously generated from various
biomedical devices and experiments due to the rapid technological advancement in medical …
biomedical devices and experiments due to the rapid technological advancement in medical …
A Hybrid Neuro‐Fuzzy and Feature Reduction Model for Classification
The evolvement of the fuzzy system has shown influential and successful in many universal
approximation capabilities and applications. This paper proposes a hybrid Neuro‐Fuzzy and …
approximation capabilities and applications. This paper proposes a hybrid Neuro‐Fuzzy and …