Results 11 to 20 of about 164,333 (266)
Journal of King Saud University: Computer and Information Sciences, 2020 High dimensional search space in microarray data with large number of genes and few dozen of samples increases the complexity of analysis of such databases. All the genes are not significant and hence informative genes are required to be extracted.
Rasmita Dash
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IEEE Access, 2019 Motivated by the increasing practical needs for simulation optimization of modern industrial systems, this paper proposes an efficient ranking and selection (R&S) procedure for selecting the best-simulated design from a finite set of alternatives in ...
Seon Han Choi +2 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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Portfolio Management Framework for Autonomous Stock Selection and Allocation
IEEE Access, 2022 Portfolio management is essential to reduce risks and maximize profits. It can be classified into two processes: stock selection and allocation. Stock selection identifies stocks with high expected profits, whereas stock allocation determines the ...
Jae-Seung Kim, Sang-Ho Kim, Ki-Hoon Lee
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Rank Selection in Multidimensional Data [PDF]
, 2010 Suppose we have a set of K-dimensional records stored in a general purpose spatial index like a K-d tree. The index efficiently supports insertions, ordinary exact searches, orthogonal range searches, nearest neighbor searches, etc. Here we consider whether we can also efficiently support search by rank, that is, to locate the i-th smallest element ...
Duch Brown, Amalia +2 more
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Hierarchical Ranking for Answer Selection
CoRR, 2021 Answer selection is a task to choose the positive answers from a pool of candidate answers for a given question. In this paper, we propose a novel strategy for answer selection, called hierarchical ranking. We introduce three levels of ranking: point-level ranking, pair-level ranking, and list-level ranking. They formulate their optimization objectives
Hang Gao 0003 +3 more
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Variable ranking and selection with random forest for unbalanced data
Environmental Data Science, 2022 When one or several classes are much less prevalent than another class (unbalanced data), class error rates and variable importances of the machine learning algorithm random forest can be biased, particularly when sample sizes are smaller, imbalance ...
Ute Bradter +5 more
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A New Method for Project Ranking Based on Risk Management and Multicriteria Approach [PDF]
European Project Management Journal, 2020 Project portfolio selection and projects ranking represent difficult decisions in organizations due to many factors. One of the most important of these factors is varying levels of projects risk.
Mahdi Nakhaeinejad
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Toward optimal feature selection using ranking methods and classification algorithms [PDF]
Yugoslav Journal of Operations Research, 2011 We presented a comparison between several feature ranking methods used on two real datasets. We considered six ranking methods that can be divided into two broad categories: statistical and entropy-based.
Novaković Jasmina +2 more
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Automatic vowels selection and ranking in Russian enciphered texts
Открытое образование (Москва), 2018 This work was developed while teaching students the cryptanalysis. The course includes the study of statistics of (Russian encrypted) texts. The purpose of training is to learn how to extract redundant information of the text and to descript the ...
Yuri I. Petrenko
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