En-MinWhale: An ensemble approach based on MRMR and Whale optimization for Cancer diagnosis
According to the WHO, Cancer is a prominent cause of mortality worldwide, accounting for~
10 million fatalities at the end of 2020. The most common types of cancers include Lung …
10 million fatalities at the end of 2020. The most common types of cancers include Lung …
Hybrid particle swarm optimization with spiral-shaped mechanism for feature selection
K Chen, FY Zhou, XF Yuan - Expert Systems with Applications, 2019 - Elsevier
The “curse of dimensionality” is one of the largest problems that influences the quality of the
optimization process in most data mining, pattern recognition, and machine learning tasks …
optimization process in most data mining, pattern recognition, and machine learning tasks …
Hybrid feature selection of breast cancer gene expression microarray data based on metaheuristic methods: A comprehensive review
Breast cancer (BC) remains the most dominant cancer among women worldwide. Numerous
BC gene expression microarray-based studies have been employed in cancer classification …
BC gene expression microarray-based studies have been employed in cancer classification …
Genetic algorithm based cancerous gene identification from microarray data using ensemble of filter methods
Microarray datasets play a crucial role in cancer detection. But the high dimension of these
datasets makes the classification challenging due to the presence of many irrelevant and …
datasets makes the classification challenging due to the presence of many irrelevant and …
Recursive memetic algorithm for gene selection in microarray data
Feature selection algorithm contributes a lot in the domain of medical diagnosis. Choosing a
small subset of genes that enable a classifier to predict the presence or type of disease …
small subset of genes that enable a classifier to predict the presence or type of disease …
Optimizing gene selection and cancer classification with hybrid sine cosine and cuckoo search algorithm
Gene expression datasets offer a wide range of information about various biological
processes. However, it is difficult to find the important genes among the high-dimensional …
processes. However, it is difficult to find the important genes among the high-dimensional …
Intelligent forecasting model of stock price using neighborhood rough set and multivariate empirical mode decomposition
J Bai, J Guo, B Sun, Y Guo, Q Bao, X **ao - Engineering Applications of …, 2023 - Elsevier
Intelligent forecasting model of stock price is an effective way to obtain ideal investment
returns. Due to the impact of quantitative transactions, traditional forecasting methods face …
returns. Due to the impact of quantitative transactions, traditional forecasting methods face …
Improving breast cancer classification with mRMR+ SS0+ WSVM: a hybrid approach
A Yaqoob, NK Verma, RM Aziz - Multimedia Tools and Applications, 2024 - Springer
Detecting breast cancer through histopathological images is time-consuming due to their
volume and complexity. Speeding up early detection is crucial for timely medical …
volume and complexity. Speeding up early detection is crucial for timely medical …
Simulated annealing aided genetic algorithm for gene selection from microarray data
S Marjit, T Bhattacharyya, B Chatterjee… - Computers in Biology and …, 2023 - Elsevier
In recent times, microarray gene expression datasets have gained significant popularity due
to their usefulness to identify different types of cancer directly through bio-markers. These …
to their usefulness to identify different types of cancer directly through bio-markers. These …
Hybrid fast unsupervised feature selection for high-dimensional data
The emergence of``curse of dimensionality” issue as a result of high reduces datasets
deteriorates the capability of learning algorithms, and also requires high memory and …
deteriorates the capability of learning algorithms, and also requires high memory and …