Results 31 to 40 of about 102,167 (290)
The Feature Importance Ranking Measure [PDF]
, 2009 15 pages, 3 figures. to appear in the Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD ...
Alexander Zien +3 more
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Feature importance ranking from RF.
, 2022 Feature importance ranking from RF.
Yuge Li (13511948) +6 more
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Number of Instances for Reliable Feature Ranking in a Given Problem
Business Systems Research, 2018 Background: In practical use of machine learning models, users may add new features to an existing classification model, reflecting their (changed) empirical understanding of a field. New features potentially increase classification accuracy of the model
Bohanec Marko +2 more
doaj +1 more source
Feature-enriched author ranking in incomplete networks
Applied Network Science, 2019 Evaluating scientists based on their scientific production is a controversial topic. Nevertheless, bibliometrics and algorithmic approaches can assist traditional peer review in numerous tasks, such as attributing research grants, deciding scientific ...
Jorge Silva +2 more
doaj +1 more source
Online Learning to Rank with Features
CoRR, 2018 We introduce a new model for online ranking in which the click probability factors into an examination and attractiveness function and the attractiveness function is a linear function of a feature vector and an unknown parameter. Only relatively mild assumptions are made on the examination function. A novel algorithm for this setup is analysed, showing
Shuai Li 0010 +2 more
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Fast Feature Ranking Algorithm [PDF]
, 2003 The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simpler and easy to understand. The algorithm has some interesting characteristics: lower computational cost (O(m n log n) m attributes and n examples in the data set) with respect ...
Roberto Ruiz +2 more
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Analysis of Feature Rankings for Classification [PDF]
, 2005 Different ways of contrast generated rankings by feature selection algorithms are presented in this paper, showing several possible interpretations, depending on the given approach to each study. We begin from the premise of no existence of only one ideal subset for all cases.
Roberto Ruiz +3 more
openaire +3 more sources
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
doaj +1 more source
Classification with correlated features: unreliability of feature ranking and solutions [PDF]
Bioinformatics, 2011 AbstractMotivation: Classification and feature selection of genomics or transcriptomics data is often hampered by the large number of features as compared with the small number of samples available. Moreover, features represented by probes that either have similar molecular functions (gene expression analysis) or genomic locations (DNA copy number ...
Tolosi, L., Lengauer, T.
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Application of Biological Domain Knowledge Based Feature Selection on Gene Expression Data
Entropy, 2020 In the last two decades, there have been massive advancements in high throughput technologies, which resulted in the exponential growth of public repositories of gene expression datasets for various phenotypes.
Malik Yousef +2 more
doaj +1 more source