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Description
| - Among the non-classical solutions of classification tasks belong approaches inspired by biological systems, such as social behavior observed in communities of insects - bees, termites, ants - and known as swarm intelligence. An algorithm based on agents that simulate the natural behavior of ants, including mechanisms of cooperation and adaption, was first published in 2001 as AntMiner. Since then several variants of this algorithm have been created, that differ in definition of quality criterion, in the rule for pheromone updating, in the way of rule pruning or in discretization method of continuous attributes. The algorithms were tested on a number of databases. It was determined that the accuracy of the classification algorithm is affected by properties of databases examined, such as number of instances, number and type of attributes, and other. In the contribution the influence of parameters of the algorithm as the number of ants, the minimum number of cases per rule or the maximum number of uncovered cases in the training set is discussed.
- Among the non-classical solutions of classification tasks belong approaches inspired by biological systems, such as social behavior observed in communities of insects - bees, termites, ants - and known as swarm intelligence. An algorithm based on agents that simulate the natural behavior of ants, including mechanisms of cooperation and adaption, was first published in 2001 as AntMiner. Since then several variants of this algorithm have been created, that differ in definition of quality criterion, in the rule for pheromone updating, in the way of rule pruning or in discretization method of continuous attributes. The algorithms were tested on a number of databases. It was determined that the accuracy of the classification algorithm is affected by properties of databases examined, such as number of instances, number and type of attributes, and other. In the contribution the influence of parameters of the algorithm as the number of ants, the minimum number of cases per rule or the maximum number of uncovered cases in the training set is discussed. (en)
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Title
| - Classification Rule Extracting with Ant Colony Algorithms
- Classification Rule Extracting with Ant Colony Algorithms (en)
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skos:prefLabel
| - Classification Rule Extracting with Ant Colony Algorithms
- Classification Rule Extracting with Ant Colony Algorithms (en)
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skos:notation
| - RIV/60461373:22340/12:43893282!RIV13-MSM-22340___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/60461373:22340/12:43893282
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - machine learning; multiagent system; classification rules; knowledge discovery; ant colony algorithms (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - 39th International Conference of Slovak Society of Chemical Engineering
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Hanta, Vladimír
- Poživil, Jaroslav
- Seidlová, Romana
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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http://linked.open...n/vavai/riv/zamer
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number of pages
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http://purl.org/ne...btex#hasPublisher
| - Slovak Society of Chemical Engineering
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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