A study on metaheuristics approaches for gene selection in microarray data: algorithms, applications and open challenges
In the recent decades, researchers have introduced an abundance of feature selection
methods many of which are studied and analyzed over the high dimensional datasets …
methods many of which are studied and analyzed over the high dimensional datasets …
Credit scoring models using ensemble learning and classification approaches: a comprehensive survey
Credit scoring models are developed to strengthen the decision-making process specifically
for financial institutions to deal with risk associated with a credit candidate while applying for …
for financial institutions to deal with risk associated with a credit candidate while applying for …
Evolutionary extreme learning machine with novel activation function for credit scoring
The term credit scoring is extensively used in credit industries for decision making and
measuring the risk associated with an applicant. It uses applicants' historical data for credit …
measuring the risk associated with an applicant. It uses applicants' historical data for credit …
A new hybrid wrapper TLBO and SA with SVM approach for gene expression data
Gene expression dataset contains a small number of tissues and thousands or tens of
thousands of noisy and redundant genes. This can lead to possibly overfitting and curse of …
thousands of noisy and redundant genes. This can lead to possibly overfitting and curse of …
Making deep learning-based predictions for credit scoring explainable
X Dastile, T Celik - IEEE Access, 2021 - ieeexplore.ieee.org
Credit scoring has become an important risk management tool for money lending
institutions. Over the years, statistical and classical machine learning models have been the …
institutions. Over the years, statistical and classical machine learning models have been the …
Obesity Prediction with EHR Data: A deep learning approach with interpretable elements
Childhood obesity is a major public health challenge. Early prediction and identification of
the children at an elevated risk of developing childhood obesity may help in engaging …
the children at an elevated risk of developing childhood obesity may help in engaging …
Enhanced evolutionary feature selection and ensemble method for cardiovascular disease prediction
V Jothi Prakash, NK Karthikeyan - … Sciences: Computational Life Sciences, 2021 - Springer
Cardiovascular Disease (CVD) is one among the main factors for the increase in mortality
rate worldwide. The analysis and prediction of this disease is yet a highly formidable task in …
rate worldwide. The analysis and prediction of this disease is yet a highly formidable task in …
A two-stage gene selection method for biomarker discovery from microarray data for cancer classification
The microarrays permit experts to monitor the gene profiling for thousands of genes across
an array of cellular responses, phenotype, and circumstances. Selecting a tiny subset of …
an array of cellular responses, phenotype, and circumstances. Selecting a tiny subset of …
A novel hybrid credit scoring model based on ensemble feature selection and multilayer ensemble classification
Credit scoring focuses on the development of empirical models to support the financial
decision‐making processes of financial institutions and credit industries. It makes use of …
decision‐making processes of financial institutions and credit industries. It makes use of …
Experimental analysis of machine learning methods for credit score classification
Credit scoring concerns with emerging empirical model to assist the financial institutions for
financial decision-making process. Credit risk analysis plays a vital role for decision-making …
financial decision-making process. Credit risk analysis plays a vital role for decision-making …