A review of feature selection methods for machine learning-based disease risk prediction
N Pudjihartono, T Fadason, AW Kempa-Liehr… - Frontiers in …, 2022 - frontiersin.org
Machine learning has shown utility in detecting patterns within large, unstructured, and
complex datasets. One of the promising applications of machine learning is in precision …
complex datasets. One of the promising applications of machine learning is in precision …
A Complete Process of Text Classification System Using State‐of‐the‐Art NLP Models
With the rapid advancement of information technology, online information has been
exponentially growing day by day, especially in the form of text documents such as news …
exponentially growing day by day, especially in the form of text documents such as news …
[HTML][HTML] Benchmark for filter methods for feature selection in high-dimensional classification data
Feature selection is one of the most fundamental problems in machine learning and has
drawn increasing attention due to high-dimensional data sets emerging from different fields …
drawn increasing attention due to high-dimensional data sets emerging from different fields …
[HTML][HTML] Ensemble machine learning approach for classification of IoT devices in smart home
The emergence of the Internet of Things (IoT) concept as a new direction of technological
development raises new problems such as valid and timely identification of such devices …
development raises new problems such as valid and timely identification of such devices …
Correlation feature selection based improved-binary particle swarm optimization for gene selection and cancer classification
DNA microarray technology has emerged as a prospective tool for diagnosis of cancer and
its classification. It provides better insights of many genetic mutations occurring within a cell …
its classification. It provides better insights of many genetic mutations occurring within a cell …
Benchmark of filter methods for feature selection in high-dimensional gene expression survival data
A Bommert, T Welchowski, M Schmid… - Briefings in …, 2022 - academic.oup.com
Feature selection is crucial for the analysis of high-dimensional data, but benchmark studies
for data with a survival outcome are rare. We compare 14 filter methods for feature selection …
for data with a survival outcome are rare. We compare 14 filter methods for feature selection …
Approaches to multi-objective feature selection: a systematic literature review
Feature selection has gained much consideration from scholars working in the domain of
machine learning and data mining in recent years. Feature selection is a popular problem in …
machine learning and data mining in recent years. Feature selection is a popular problem in …
基于随机森林的特征选择算法
姚登举， 杨静， 詹晓娟 - 吉林大学学报(工学版), 2014 - xuebao.jlu.edu.cn
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[PDF][PDF] Feature selection for classification: A review
Nowadays, the growth of the high-throughput technologies has resulted in exponential
growth in the harvested data with respect to both dimensionality and sample size. The trend …
growth in the harvested data with respect to both dimensionality and sample size. The trend …
Recent advances in feature selection and its applications
Feature selection is one of the key problems for machine learning and data mining. In this
review paper, a brief historical background of the field is given, followed by a selection of …
review paper, a brief historical background of the field is given, followed by a selection of …