IMMAN: free software for information theory-based chemometric analysis
Abstract: The features and theoretical background of a new and free computational program for chemometric analysis denominated IMMAN (acronym for Information theory-based CheMoMetrics ANalysis) are presented. This is multi-platform software developed in the Java programming language, designed with a...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2015
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9015
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9015
- Palabra clave:
- Chemometric analysis
Classification
Computational program
Feature selection
IMMAN
Information-theoretic function
Algorithm
Software
Theoretical model
Algorithms
Models, Theoretical
Software
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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IMMAN: free software for information theory-based chemometric analysis |
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IMMAN: free software for information theory-based chemometric analysis |
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IMMAN: free software for information theory-based chemometric analysis Chemometric analysis Classification Computational program Feature selection IMMAN Information-theoretic function Algorithm Software Theoretical model Algorithms Models, Theoretical Software |
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IMMAN: free software for information theory-based chemometric analysis |
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IMMAN: free software for information theory-based chemometric analysis |
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IMMAN: free software for information theory-based chemometric analysis |
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IMMAN: free software for information theory-based chemometric analysis |
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IMMAN: free software for information theory-based chemometric analysis |
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Chemometric analysis Classification Computational program Feature selection IMMAN Information-theoretic function Algorithm Software Theoretical model Algorithms Models, Theoretical Software |
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Chemometric analysis Classification Computational program Feature selection IMMAN Information-theoretic function Algorithm Software Theoretical model Algorithms Models, Theoretical Software |
| description |
Abstract: The features and theoretical background of a new and free computational program for chemometric analysis denominated IMMAN (acronym for Information theory-based CheMoMetrics ANalysis) are presented. This is multi-platform software developed in the Java programming language, designed with a remarkably user-friendly graphical interface for the computation of a collection of information-theoretic functions adapted for rank-based unsupervised and supervised feature selection tasks. A total of 20 feature selection parameters are presented, with the unsupervised and supervised frameworks represented by 10 approaches in each case. Several information-theoretic parameters traditionally used as molecular descriptors (MDs) are adapted for use as unsupervised rank-based feature selection methods. On the other hand, a generalization scheme for the previously defined differential Shannon’s entropy is discussed, as well as the introduction of Jeffreys information measure for supervised feature selection. Moreover, well-known information-theoretic feature selection parameters, such as information gain, gain ratio, and symmetrical uncertainty are incorporated to the IMMAN software (http://mobiosd-hub.com/imman-soft/), following an equal-interval discretization approach. IMMAN offers data pre-processing functionalities, such as missing values processing, dataset partitioning, and browsing. Moreover, single parameter or ensemble (multi-criteria) ranking options are provided. Consequently, this software is suitable for tasks like dimensionality reduction, feature ranking, as well as comparative diversity analysis of data matrices. Simple examples of applications performed with this program are presented. A comparative study between IMMAN and WEKA feature selection tools using the Arcene dataset was performed, demonstrating similar behavior. In addition, it is revealed that the use of IMMAN unsupervised feature selection methods improves the performance of both IMMAN and WEKA supervised algorithms. © 2015, Springer International Publishing Switzerland. |
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2015 |
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2015 |
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2020-03-26T16:32:46Z |
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Artículo |
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Molecular Diversity; Vol. 19, Núm. 2; pp. 305-319 |
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13811991 |
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https://hdl.handle.net/20.500.12585/9015 |
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10.1007/s11030-014-9565-z |
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Universidad Tecnológica de Bolívar |
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Repositorio UTB |
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Molecular Diversity; Vol. 19, Núm. 2; pp. 305-319 13811991 10.1007/s11030-014-9565-z Universidad Tecnológica de Bolívar Repositorio UTB 56497011800 55363486500 55665599200 56189852800 56191215400 6701762262 |
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https://hdl.handle.net/20.500.12585/9015 |
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eng |
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eng |
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2020-03-26T16:32:46Z2020-03-26T16:32:46Z2015Molecular Diversity; Vol. 19, Núm. 2; pp. 305-31913811991https://hdl.handle.net/20.500.12585/901510.1007/s11030-014-9565-zUniversidad Tecnológica de BolívarRepositorio UTB56497011800553634865005566559920056189852800561912154006701762262Abstract: The features and theoretical background of a new and free computational program for chemometric analysis denominated IMMAN (acronym for Information theory-based CheMoMetrics ANalysis) are presented. This is multi-platform software developed in the Java programming language, designed with a remarkably user-friendly graphical interface for the computation of a collection of information-theoretic functions adapted for rank-based unsupervised and supervised feature selection tasks. A total of 20 feature selection parameters are presented, with the unsupervised and supervised frameworks represented by 10 approaches in each case. Several information-theoretic parameters traditionally used as molecular descriptors (MDs) are adapted for use as unsupervised rank-based feature selection methods. On the other hand, a generalization scheme for the previously defined differential Shannon’s entropy is discussed, as well as the introduction of Jeffreys information measure for supervised feature selection. Moreover, well-known information-theoretic feature selection parameters, such as information gain, gain ratio, and symmetrical uncertainty are incorporated to the IMMAN software (http://mobiosd-hub.com/imman-soft/), following an equal-interval discretization approach. IMMAN offers data pre-processing functionalities, such as missing values processing, dataset partitioning, and browsing. Moreover, single parameter or ensemble (multi-criteria) ranking options are provided. Consequently, this software is suitable for tasks like dimensionality reduction, feature ranking, as well as comparative diversity analysis of data matrices. Simple examples of applications performed with this program are presented. A comparative study between IMMAN and WEKA feature selection tools using the Arcene dataset was performed, demonstrating similar behavior. In addition, it is revealed that the use of IMMAN unsupervised feature selection methods improves the performance of both IMMAN and WEKA supervised algorithms. © 2015, Springer International Publishing Switzerland.Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPqRecurso electrónicoapplication/pdfengKluwer Academic Publishershttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84937517073&doi=10.1007%2fs11030-014-9565-z&partnerID=40&md5=bebd134ed45279902c02db40eaa3b28cIMMAN: free software for information theory-based chemometric analysisinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Chemometric analysisClassificationComputational programFeature selectionIMMANInformation-theoretic functionAlgorithmSoftwareTheoretical modelAlgorithmsModels, TheoreticalSoftwareUrias R.W.P.Barigye S.J.Marrero-Ponce Y.García-Jacas C.R.Valdes-Martiní J.R.Perez-Gimenez F.Todeschini, R., Consonni, V., (2009) Molecular descriptors for chemoinformatics, , 1, Wiley-VCH, Weinheim:Todeschini, R., Consonni, V., Pavan, M., DRAGON Software version 2.1. 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