A review of dimensionality reduction techniques for efficient computation
S Velliangiri, S Alagumuthukrishnan - Procedia Computer Science, 2019 - Elsevier
Dimensionality Reduction (DR) is the pre-processing step to remove redundant features,
noisy and irrelevant data, in order to improve learning feature accuracy and reduce the …
noisy and irrelevant data, in order to improve learning feature accuracy and reduce the …
A survey of feature selection and feature extraction techniques in machine learning
Dimensionality reduction as a preprocessing step to machine learning is effective in
removing irrelevant and redundant data, increasing learning accuracy, and improving result …
removing irrelevant and redundant data, increasing learning accuracy, and improving result …
Artificial intelligence and its application in the prediction and diagnosis of animal diseases: A review
AZA Ali - Indian Journal of Animal Research, 2023 - indianjournals.com
The role of artificial intelligence (AI) in veterinary science is becoming increasingly important
as the technology advances. AI applications have the potential to revolutionize the …
as the technology advances. AI applications have the potential to revolutionize the …
[HTML][HTML] Machine learning-based diagnosis of breast cancer utilizing feature optimization technique
Breast cancer disease is recognized as one of the leading causes of death in women
worldwide after lung cancer. Breast cancer refers to a malignant neoplasm that develops …
worldwide after lung cancer. Breast cancer refers to a malignant neoplasm that develops …
[HTML][HTML] A linear discriminant analysis and classification model for breast cancer diagnosis
MO Adebiyi, MO Arowolo, MD Mshelia, OO Olugbara - Applied Sciences, 2022 - mdpi.com
Although most cases are identified at a late stage, breast cancer is the most public
malignancy amongst women globally. However, mammography for the analysis of breast …
malignancy amongst women globally. However, mammography for the analysis of breast …
[HTML][HTML] Vocal feature extraction-based artificial intelligent model for Parkinson's disease detection
As a neurodegenerative disorder, Parkinson's disease (PD) affects the nerve cells of the
human brain. Early detection and treatment can help to relieve the symptoms of PD. Recent …
human brain. Early detection and treatment can help to relieve the symptoms of PD. Recent …
[HTML][HTML] Classifier performance evaluation for lightweight IDS using fog computing in IoT security
In this article, a Host-Based Intrusion Detection System (HIDS) using a Modified Vector
Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing …
Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing …
[HTML][HTML] Feature selection and transformation by machine learning reduce variable numbers and improve prediction for heart failure readmission or death
Background The prediction of readmission or death after a hospital discharge for heart
failure (HF) remains a major challenge. Modern healthcare systems, electronic health …
failure (HF) remains a major challenge. Modern healthcare systems, electronic health …
[HTML][HTML] Evaluation of three feature dimension reduction techniques for machine learning-based crop yield prediction models
Machine learning (ML) has been widely used worldwide to develop crop yield forecasting
models. However, it is still challenging to identify the most critical features from a dataset …
models. However, it is still challenging to identify the most critical features from a dataset …
A Multilayer Perceptron Neural Network Model to Classify Hypertension in Adolescents Using Anthropometric Measurements: A Cross‐Sectional Study in Sarawak …
This study outlines and developed a multilayer perceptron (MLP) neural network model for
adolescent hypertension classification focusing on the use of simple anthropometric and …
adolescent hypertension classification focusing on the use of simple anthropometric and …