Results 31 to 40 of about 1,793,798 (289)
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
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Learning to Rank 3D Features [PDF]
, 2014 Representation of three dimensional objects using a set of oriented point pair features has been shown to be effective for object recognition and pose estimation. Combined with an efficient voting scheme on a generalized Hough space, existing approaches achieve good recognition accuracy and fast operation.
Oncel Tuzel +3 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
openaire +2 more sources
Predicting Diabetes Mellitus With Machine Learning Techniques
Frontiers in Genetics, 2018 Diabetes mellitus is a chronic disease characterized by hyperglycemia. It may cause many complications. According to the growing morbidity in recent years, in 2040, the world’s diabetic patients will reach 642 million, which means that one of the ten ...
Quan Zou +6 more
doaj +1 more source
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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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 +4 more sources
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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The quantum probability ranking principle for information retrieval [PDF]
, 2009 While the Probability Ranking Principle for Information Retrieval provides the basis for formal models, it makes a very strong assumption regarding the dependence between documents.
Van Rijsbergen, C. +8 more
core +3 more sources
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
Wrapper for Ranking Feature Selection [PDF]
, 2004 We propose a new feature selection criterion not based on calculated measures between attributes, or complex and costly distance calculations. Applying a wrapper to the output of a new attribute ranking method, we obtain a minimum subset with the same error rate as the original data.
Roberto Ruiz +2 more
openaire +3 more sources