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Software feature extraction using infrequent feature extraction
2016 6th International Annual Engineering Seminar (InAES), 2016Evolution and maintenance processes are important but time consuming and expensive. It is very important to make the processes effective and efficient. A software developer can use resource like user opinion data to get information, such as user request, bug report, and user experience.
Divi Galih Prasetyo Putri +1 more
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2018
This chapter is an illustration of feature extraction for working with large datasets. The basic definition of feature extraction, selection of effective features, and the existing problems and solutions are provided. How feature extraction maps the high dimensional space to smaller space is explained.
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This chapter is an illustration of feature extraction for working with large datasets. The basic definition of feature extraction, selection of effective features, and the existing problems and solutions are provided. How feature extraction maps the high dimensional space to smaller space is explained.
openaire +2 more sources
2017
Accessibility problem is relevant for audiovisual information, where enormous data has to be explored and processed. Most of the solutions for this specific type of problems point towards a regular need of extracting applicable information features for a given content domain.
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Accessibility problem is relevant for audiovisual information, where enormous data has to be explored and processed. Most of the solutions for this specific type of problems point towards a regular need of extracting applicable information features for a given content domain.
+4 more sources
Feature Extraction Through LOCOCODE
Neural Computation, 1999Low-complexity coding and decoding (LOCOCODE) is a novel approach to sensory coding and unsupervised learning. Unlike previous methods, it explicitly takes into account the information-theoretic complexity of the code generator. It computes lococodes that convey information about the input data and can be computed and decoded by low-complexity ...
S, Hochreiter, J, Schmidhuber
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Redundancy in Feature Extraction
IEEE Transactions on Computers, 1971Given two random variables X and Y, a definition is offered that gives a condition for Y to be redundant with respect to X. It is shown that if such redundancy exists, then observations on Y, i.e., pattern vector elements related to Y, can be eliminated without increasing the classification error.
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