FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2023984830> ?p ?o ?g. }

• W2023984830 endingPage "540" @default.
• W2023984830 startingPage "533" @default.
• W2023984830 abstract "We investigate the multiclass classification of cancer microarray samples. In contrast to classification of two cancer types from gene expression data, multiclass classification of more than two cancer types are relatively hard and less studied problem. We used class-wise optimized genes with corresponding one-versus-all support vector machine (OVA-SVM) classifier to maximize the utilization of selected genes. Final prediction was made by using probability scores from all classifiers. We used three different methods of estimating probability from decision value. Among the three probability methods, Platt's approach was more consistent, whereas, isotonic approach performed better for datasets with unequal proportion of samples in different classes. Probability based decision does not only gives true and fair comparison between different one-versus-all (OVA) classifiers but also gives the possibility of using them for any post analysis. Several ensemble experiments, an example of post analysis, of the three probability methods were implemented to study their effect in improving the classification accuracy. We observe that ensemble did help in improving the predictive accuracy of cancer data sets especially involving unbalanced samples. Four-fold external stratified cross-validation experiment was performed on the six multiclass cancer datasets to obtain unbiased estimates of prediction accuracies. Analysis of class-wise frequently selected genes on two cancer datasets demonstrated that the approach was able to select important and relevant genes consistent to literature. This study demonstrates successful implementation of the framework of class-wise feature selection and multiclass classification for prediction of cancer subtypes on six datasets." @default.
• W2023984830 created "2016-06-24" @default.
• W2023984830 creator A5025626208 @default.
• W2023984830 creator A5040626471 @default.
• W2023984830 date "2009-08-01" @default.
• W2023984830 modified "2023-09-25" @default.
• W2023984830 title "Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates" @default.
• W2023984830 cites W1498268535 @default.
• W2023984830 cites W1727290854 @default.
• W2023984830 cites W1864170427 @default.
• W2023984830 cites W1963516639 @default.
• W2023984830 cites W1976093800 @default.
• W2023984830 cites W1977316223 @default.
• W2023984830 cites W1977489168 @default.
• W2023984830 cites W1977927254 @default.
• W2023984830 cites W1980256262 @default.
• W2023984830 cites W1981532526 @default.
• W2023984830 cites W1982276763 @default.
• W2023984830 cites W1984511561 @default.
• W2023984830 cites W1986853856 @default.
• W2023984830 cites W1987713050 @default.
• W2023984830 cites W1988907693 @default.
• W2023984830 cites W1989076816 @default.
• W2023984830 cites W1995143646 @default.
• W2023984830 cites W2008634847 @default.
• W2023984830 cites W2012942264 @default.
• W2023984830 cites W2016511206 @default.
• W2023984830 cites W2020969907 @default.
• W2023984830 cites W2026666393 @default.
• W2023984830 cites W2030571354 @default.
• W2023984830 cites W2036956828 @default.
• W2023984830 cites W2037472196 @default.
• W2023984830 cites W2037838449 @default.
• W2023984830 cites W2042124637 @default.
• W2023984830 cites W2053429233 @default.
• W2023984830 cites W2053963319 @default.
• W2023984830 cites W2063122849 @default.
• W2023984830 cites W2069389043 @default.
• W2023984830 cites W2073718013 @default.
• W2023984830 cites W2075414949 @default.
• W2023984830 cites W2077208354 @default.
• W2023984830 cites W2077538414 @default.
• W2023984830 cites W2080915318 @default.
• W2023984830 cites W2089440068 @default.
• W2023984830 cites W2090642125 @default.
• W2023984830 cites W2097413644 @default.
• W2023984830 cites W2107956883 @default.
• W2023984830 cites W2109363337 @default.
• W2023984830 cites W2111174230 @default.
• W2023984830 cites W2115358726 @default.
• W2023984830 cites W2116079122 @default.
• W2023984830 cites W2117135012 @default.
• W2023984830 cites W2120026469 @default.
• W2023984830 cites W2122128696 @default.
• W2023984830 cites W2133671203 @default.
• W2023984830 cites W2137476312 @default.
• W2023984830 cites W2137721361 @default.
• W2023984830 cites W2138550913 @default.
• W2023984830 cites W2141873373 @default.
• W2023984830 cites W2143426320 @default.
• W2023984830 cites W2151180344 @default.
• W2023984830 cites W2155236584 @default.
• W2023984830 cites W2155312231 @default.
• W2023984830 cites W2155612034 @default.
• W2023984830 cites W2167456918 @default.
• W2023984830 cites W2172000360 @default.
• W2023984830 cites W238668910 @default.
• W2023984830 cites W4246697467 @default.
• W2023984830 cites W4252536204 @default.
• W2023984830 doi "https://doi.org/10.1016/j.jtbi.2009.04.013" @default.
• W2023984830 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19406131" @default.
• W2023984830 hasPublicationYear "2009" @default.
• W2023984830 type Work @default.
• W2023984830 sameAs 2023984830 @default.
• W2023984830 citedByCount "32" @default.
• W2023984830 countsByYear W20239848302012 @default.
• W2023984830 countsByYear W20239848302013 @default.
• W2023984830 countsByYear W20239848302014 @default.
• W2023984830 countsByYear W20239848302015 @default.
• W2023984830 countsByYear W20239848302016 @default.
• W2023984830 countsByYear W20239848302017 @default.
• W2023984830 countsByYear W20239848302018 @default.
• W2023984830 countsByYear W20239848302019 @default.
• W2023984830 countsByYear W20239848302020 @default.
• W2023984830 countsByYear W20239848302022 @default.
• W2023984830 crossrefType "journal-article" @default.
• W2023984830 hasAuthorship W2023984830A5025626208 @default.
• W2023984830 hasAuthorship W2023984830A5040626471 @default.
• W2023984830 hasConcept C119857082 @default.
• W2023984830 hasConcept C12267149 @default.
• W2023984830 hasConcept C123860398 @default.
• W2023984830 hasConcept C124101348 @default.
• W2023984830 hasConcept C148483581 @default.
• W2023984830 hasConcept C153180895 @default.
• W2023984830 hasConcept C154945302 @default.
• W2023984830 hasConcept C33923547 @default.
• W2023984830 hasConcept C41008148 @default.
• W2023984830 hasConcept C95623464 @default.

• next