FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2005604830> ?p ?o ?g. }

• W2005604830 endingPage "263" @default.
• W2005604830 startingPage "247" @default.
• W2005604830 abstract "In function approximation problems, one of the most common ways to evaluate a learning algorithm consists in partitioning the original data set (input/output data) into two sets: learning, used for building models, and test, applied for genuine out-of-sample evaluation. When the partition into learning and test sets does not take into account the variability and geometry of the original data, it might lead to non-balanced and unrepresentative learning and test sets and, thus, to wrong conclusions in the accuracy of the learning algorithm. How the partitioning is made is therefore a key issue and becomes more important when the data set is small due to the need of reducing the pessimistic effects caused by the removal of instances from the original data set. Thus, in this work, we propose a deterministic data mining approach for a distribution of a data set (input/output data) into two representative and balanced sets of roughly equal size taking the variability of the data set into consideration with the purpose of allowing both a fair evaluation of learning's accuracy and to make reproducible machine learning experiments usually based on random distributions. The sets are generated using a combination of a clustering procedure, especially suited for function approximation problems, and a distribution algorithm which distributes the data set into two sets within each cluster based on a nearest-neighbor approach. In the experiments section, the performance of the proposed methodology is reported in a variety of situations through an ANOVA-based statistical study of the results." @default.
• W2005604830 created "2016-06-24" @default.
• W2005604830 creator A5039951150 @default.
• W2005604830 creator A5084085925 @default.
• W2005604830 creator A5089029287 @default.
• W2005604830 date "2011-06-01" @default.
• W2005604830 modified "2023-10-14" @default.
• W2005604830 title "GENERATING BALANCED LEARNING AND TEST SETS FOR FUNCTION APPROXIMATION PROBLEMS" @default.
• W2005604830 cites W1496317909 @default.
• W2005604830 cites W1592988488 @default.
• W2005604830 cites W1601895673 @default.
• W2005604830 cites W1758072178 @default.
• W2005604830 cites W1965555277 @default.
• W2005604830 cites W1966859905 @default.
• W2005604830 cites W1971806422 @default.
• W2005604830 cites W1978231456 @default.
• W2005604830 cites W1991635091 @default.
• W2005604830 cites W1992918127 @default.
• W2005604830 cites W2001860992 @default.
• W2005604830 cites W2002430706 @default.
• W2005604830 cites W2008973833 @default.
• W2005604830 cites W2028072219 @default.
• W2005604830 cites W2035127367 @default.
• W2005604830 cites W2037102194 @default.
• W2005604830 cites W2037984448 @default.
• W2005604830 cites W2066082689 @default.
• W2005604830 cites W2078128010 @default.
• W2005604830 cites W2088370125 @default.
• W2005604830 cites W2092292464 @default.
• W2005604830 cites W2092429479 @default.
• W2005604830 cites W2094631910 @default.
• W2005604830 cites W2102892532 @default.
• W2005604830 cites W2108400241 @default.
• W2005604830 cites W2110485445 @default.
• W2005604830 cites W2111527217 @default.
• W2005604830 cites W2113771037 @default.
• W2005604830 cites W2116119284 @default.
• W2005604830 cites W2120199131 @default.
• W2005604830 cites W2124450561 @default.
• W2005604830 cites W2125566231 @default.
• W2005604830 cites W2128758417 @default.
• W2005604830 cites W2133267871 @default.
• W2005604830 cites W2134984799 @default.
• W2005604830 cites W2138484437 @default.
• W2005604830 cites W2146972303 @default.
• W2005604830 cites W2149668177 @default.
• W2005604830 cites W2150583452 @default.
• W2005604830 cites W2151974325 @default.
• W2005604830 cites W2156222099 @default.
• W2005604830 cites W2158086655 @default.
• W2005604830 cites W2158994553 @default.
• W2005604830 cites W2161182098 @default.
• W2005604830 cites W2161744734 @default.
• W2005604830 cites W2171533361 @default.
• W2005604830 cites W4240691156 @default.
• W2005604830 doi "https://doi.org/10.1142/s0129065711002791" @default.
• W2005604830 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/21656926" @default.
• W2005604830 hasPublicationYear "2011" @default.
• W2005604830 type Work @default.
• W2005604830 sameAs 2005604830 @default.
• W2005604830 citedByCount "7" @default.
• W2005604830 countsByYear W20056048302012 @default.
• W2005604830 countsByYear W20056048302013 @default.
• W2005604830 countsByYear W20056048302016 @default.
• W2005604830 crossrefType "journal-article" @default.
• W2005604830 hasAuthorship W2005604830A5039951150 @default.
• W2005604830 hasAuthorship W2005604830A5084085925 @default.
• W2005604830 hasAuthorship W2005604830A5089029287 @default.
• W2005604830 hasConcept C11413529 @default.
• W2005604830 hasConcept C114614502 @default.
• W2005604830 hasConcept C119857082 @default.
• W2005604830 hasConcept C124101348 @default.
• W2005604830 hasConcept C14036430 @default.
• W2005604830 hasConcept C154945302 @default.
• W2005604830 hasConcept C16910744 @default.
• W2005604830 hasConcept C177264268 @default.
• W2005604830 hasConcept C199360897 @default.
• W2005604830 hasConcept C33923547 @default.
• W2005604830 hasConcept C41008148 @default.
• W2005604830 hasConcept C42812 @default.
• W2005604830 hasConcept C58489278 @default.
• W2005604830 hasConcept C73555534 @default.
• W2005604830 hasConcept C78458016 @default.
• W2005604830 hasConcept C86803240 @default.
• W2005604830 hasConceptScore W2005604830C11413529 @default.
• W2005604830 hasConceptScore W2005604830C114614502 @default.
• W2005604830 hasConceptScore W2005604830C119857082 @default.
• W2005604830 hasConceptScore W2005604830C124101348 @default.
• W2005604830 hasConceptScore W2005604830C14036430 @default.
• W2005604830 hasConceptScore W2005604830C154945302 @default.
• W2005604830 hasConceptScore W2005604830C16910744 @default.
• W2005604830 hasConceptScore W2005604830C177264268 @default.
• W2005604830 hasConceptScore W2005604830C199360897 @default.
• W2005604830 hasConceptScore W2005604830C33923547 @default.
• W2005604830 hasConceptScore W2005604830C41008148 @default.
• W2005604830 hasConceptScore W2005604830C42812 @default.
• W2005604830 hasConceptScore W2005604830C58489278 @default.
• W2005604830 hasConceptScore W2005604830C73555534 @default.

• next