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A comprehensive review of dimensionality reduction techniques for feature selection and feature extraction
Due to sharp increases in data dimensions, working on every data mining or machine
learning (ML) task requires more efficient techniques to get the desired results. Therefore, in …
learning (ML) task requires more efficient techniques to get the desired results. Therefore, in …
[HTML][HTML] Feature selection and classification systems for chronic disease prediction: A review
D Jain, V Singh - Egyptian Informatics Journal, 2018 - Elsevier
Abstract Chronic Disease Prediction plays a pivotal role in healthcare informatics. It is crucial
to diagnose the disease at an early stage. This paper presents a survey on the utilization of …
to diagnose the disease at an early stage. This paper presents a survey on the utilization of …
Cyber intrusion detection by combined feature selection algorithm
Due to the widespread diffusion of network connectivity, the demand for network security
and protection against cyber-attacks is ever increasing. Intrusion detection systems (IDS) …
and protection against cyber-attacks is ever increasing. Intrusion detection systems (IDS) …
A survey on semi-supervised feature selection methods
Feature selection is a significant task in data mining and machine learning applications
which eliminates irrelevant and redundant features and improves learning performance. In …
which eliminates irrelevant and redundant features and improves learning performance. In …
Supervised, unsupervised, and semi-supervised feature selection: a review on gene selection
JC Ang, A Mirzal, H Haron… - IEEE/ACM transactions …, 2015 - ieeexplore.ieee.org
Recently, feature selection and dimensionality reduction have become fundamental tools for
many data mining tasks, especially for processing high-dimensional data such as gene …
many data mining tasks, especially for processing high-dimensional data such as gene …
Optimal feature-based multi-kernel SVM approach for thyroid disease classification
Thyroid diseases are across the board around the world. In India as well, there is a critical
issue caused because of this disease. Different research studies estimate that around 42 …
issue caused because of this disease. Different research studies estimate that around 42 …
[HTML][HTML] A Random Forest based predictor for medical data classification using feature ranking
Medical data classification is considered to be a challenging task in the field of medical
informatics. Although many works have been reported in the literature, there is still scope for …
informatics. Although many works have been reported in the literature, there is still scope for …
A review of feature selection methods on synthetic data
With the advent of high dimensionality, adequate identification of relevant features of the
data has become indispensable in real-world scenarios. In this context, the importance of …
data has become indispensable in real-world scenarios. In this context, the importance of …
Breast cancer diagnosis using GA feature selection and Rotation Forest
Breast cancer is one of the primary causes of death among the women worldwide, and the
accurate diagnosis is one of the most significant steps in breast cancer treatment. Data …
accurate diagnosis is one of the most significant steps in breast cancer treatment. Data …
[HTML][HTML] A machine learning method for classification of cervical cancer
Cervical cancer is one of the leading causes of premature mortality among women
worldwide and more than 85% of these deaths are in develo** countries. There are …
worldwide and more than 85% of these deaths are in develo** countries. There are …