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Feature ranking and network analysis of global financial indices [PDF]
PLoS ONE, 2022 The feature ranking method of machine learning is applied to investigate the feature ranking and network properties of 21 world stock indices. The feature ranking is the probability of influence of each index on the target.
Mahmudul Islam Rakib +2 more
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Structure and dynamics of financial networks by feature ranking method [PDF]
Scientific Reports, 2021 Much research has been done on time series of financial market in last two decades using linear and non-linear correlation of the returns of stocks.
Mahmudul Islam Rakib +2 more
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Exploring the Influence of Pottery Jar Formula Variables on Flavor Substances Through Feature Ranking and Machine Learning: Case Study of Maotai-Flavored Baijiu [PDF]
FoodsThe advantages of pottery jars in the aging process of Baijiu are evident, but the impact of their material composition and pore structure on the flavor of Baijiu has not been widely studied. This study systematically analyzed the effects of six types of
Haili Yang +5 more
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Feature Ranking on Small Samples: A Bayes-Based Approach [PDF]
EntropyIn the modern world, there is a need to provide a better understanding of the importance or relevance of the available descriptive features for predicting target attributes to solve the feature ranking problem.
Aleksandra Vatian +2 more
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Neighborhood Ranking-Based Feature Selection
IEEE AccessThis article aims to integrate ${k}$ -NN regression, false-nearest neighborhood (FNN), and trustworthiness and continuity (T&C) neighborhood-based measures into an efficient and robust feature selection method to support the identification of ...
Adam Ipkovich, Janos Abonyi
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Linear feature extraction for ranking [PDF]
Information Retrieval Journal, 2018 We address the feature extraction problem for document ranking in information retrieval. We then propose LifeRank, a Linear feature extraction algorithm for Ranking. In LifeRank, we regard each document collection for ranking as a matrix, referred to as the original matrix.
Gaurav Pandey +4 more
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Computers, 2023 Feature selection is a crucial step in machine learning, aiming to identify the most relevant features in high-dimensional data in order to reduce the computational complexity of model development and improve generalization performance.
László Göcs, Zsolt Csaba Johanyák
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A feature selection method with feature ranking using genetic programming
Connection Science, 2022 Feature selection is a data processing method which aims to select effective feature subsets from original features. Feature selection based on evolutionary computation (EC) algorithms can often achieve better classification performance because of their ...
Guopeng Liu +3 more
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Relational Regularization and Feature Ranking [PDF]
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014 Regularization is one of the key concepts in machine learning, but so far it has received only little attention in the logical and relational learning setting. Here we propose a regularization and feature selection technique for such setting, in which one commonly represents the structure of the domain using an entity-relationship model.
Costa, Fabrizio +2 more
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Information, 2022 Globally, smart cities, infrastructure, and transportation have led to a rise in vehicle numbers, resulting in an increasing number of problems. This includes problems such as air pollution, noise pollution, high energy consumption, and people’s health ...
Manish Kumar Pandey +4 more
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