Matches in SemOpenAlex for { <https://semopenalex.org/work/W2069375627> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W2069375627 abstract "Accuracy of a classifier or predictor is normally estimated with the help of confusion matrix, which is a useful tool for analyzing how well the classifier can recognize tuples of different classes. Calculation of classification accuracy of a predictor using confusion matrix for two classed attribute is simple. In case of multi classed attribute, we have to take accuracy of all the classes into consideration, to aggregate them to come with the actual accuracy of the particular classifier or predictor for that particular attribute. Here formulating this, weighted average classification accuracy has been introduced for the overall recognition rate of the classifier, which reflects how well the classifier recognizes tuples of various classes. Classification accuracy is being calculated for the classifiers BayesNet(BN), NaiveBayes(NB), J48 and Decision Table(DT) through weighted average accuracy formulation and the trend of the accuracy values for different number of instances is displayed in tables, which shows the flawless calculation." @default.
- W2069375627 created "2016-06-24" @default.
- W2069375627 creator A5064881942 @default.
- W2069375627 creator A5085388539 @default.
- W2069375627 date "2014-08-28" @default.
- W2069375627 modified "2023-10-13" @default.
- W2069375627 title "Augmenting Weighted Average with Confusion Matrix to Enhance Classification Accuracy" @default.
- W2069375627 cites W1964252296 @default.
- W2069375627 cites W1970473112 @default.
- W2069375627 cites W1989022844 @default.
- W2069375627 cites W2028219433 @default.
- W2069375627 cites W2029597490 @default.
- W2069375627 cites W2066250437 @default.
- W2069375627 cites W2077207370 @default.
- W2069375627 cites W2091467105 @default.
- W2069375627 cites W2099069468 @default.
- W2069375627 cites W2099240225 @default.
- W2069375627 cites W2112011527 @default.
- W2069375627 cites W2140190241 @default.
- W2069375627 cites W2170306141 @default.
- W2069375627 cites W2171265988 @default.
- W2069375627 cites W2535824866 @default.
- W2069375627 cites W2536356322 @default.
- W2069375627 cites W2546190945 @default.
- W2069375627 cites W3216909112 @default.
- W2069375627 doi "https://doi.org/10.14738/tmlai.24.328" @default.
- W2069375627 hasPublicationYear "2014" @default.
- W2069375627 type Work @default.
- W2069375627 sameAs 2069375627 @default.
- W2069375627 citedByCount "15" @default.
- W2069375627 countsByYear W20693756272015 @default.
- W2069375627 countsByYear W20693756272016 @default.
- W2069375627 countsByYear W20693756272017 @default.
- W2069375627 countsByYear W20693756272019 @default.
- W2069375627 countsByYear W20693756272020 @default.
- W2069375627 countsByYear W20693756272021 @default.
- W2069375627 countsByYear W20693756272022 @default.
- W2069375627 countsByYear W20693756272023 @default.
- W2069375627 crossrefType "journal-article" @default.
- W2069375627 hasAuthorship W2069375627A5064881942 @default.
- W2069375627 hasAuthorship W2069375627A5085388539 @default.
- W2069375627 hasBestOaLocation W20693756271 @default.
- W2069375627 hasConcept C11171543 @default.
- W2069375627 hasConcept C118615104 @default.
- W2069375627 hasConcept C118930307 @default.
- W2069375627 hasConcept C119857082 @default.
- W2069375627 hasConcept C12267149 @default.
- W2069375627 hasConcept C124101348 @default.
- W2069375627 hasConcept C138602881 @default.
- W2069375627 hasConcept C153180895 @default.
- W2069375627 hasConcept C154945302 @default.
- W2069375627 hasConcept C15744967 @default.
- W2069375627 hasConcept C2781140086 @default.
- W2069375627 hasConcept C33923547 @default.
- W2069375627 hasConcept C41008148 @default.
- W2069375627 hasConcept C52001869 @default.
- W2069375627 hasConcept C52003472 @default.
- W2069375627 hasConcept C95623464 @default.
- W2069375627 hasConceptScore W2069375627C11171543 @default.
- W2069375627 hasConceptScore W2069375627C118615104 @default.
- W2069375627 hasConceptScore W2069375627C118930307 @default.
- W2069375627 hasConceptScore W2069375627C119857082 @default.
- W2069375627 hasConceptScore W2069375627C12267149 @default.
- W2069375627 hasConceptScore W2069375627C124101348 @default.
- W2069375627 hasConceptScore W2069375627C138602881 @default.
- W2069375627 hasConceptScore W2069375627C153180895 @default.
- W2069375627 hasConceptScore W2069375627C154945302 @default.
- W2069375627 hasConceptScore W2069375627C15744967 @default.
- W2069375627 hasConceptScore W2069375627C2781140086 @default.
- W2069375627 hasConceptScore W2069375627C33923547 @default.
- W2069375627 hasConceptScore W2069375627C41008148 @default.
- W2069375627 hasConceptScore W2069375627C52001869 @default.
- W2069375627 hasConceptScore W2069375627C52003472 @default.
- W2069375627 hasConceptScore W2069375627C95623464 @default.
- W2069375627 hasIssue "4" @default.
- W2069375627 hasLocation W20693756271 @default.
- W2069375627 hasLocation W20693756272 @default.
- W2069375627 hasOpenAccess W2069375627 @default.
- W2069375627 hasPrimaryLocation W20693756271 @default.
- W2069375627 hasRelatedWork W191014748 @default.
- W2069375627 hasRelatedWork W2069375627 @default.
- W2069375627 hasRelatedWork W2356966757 @default.
- W2069375627 hasRelatedWork W2563096758 @default.
- W2069375627 hasRelatedWork W2570625548 @default.
- W2069375627 hasRelatedWork W2899196211 @default.
- W2069375627 hasRelatedWork W3011378683 @default.
- W2069375627 hasRelatedWork W3160713586 @default.
- W2069375627 hasRelatedWork W3185179407 @default.
- W2069375627 hasRelatedWork W4361795583 @default.
- W2069375627 hasVolume "2" @default.
- W2069375627 isParatext "false" @default.
- W2069375627 isRetracted "false" @default.
- W2069375627 magId "2069375627" @default.
- W2069375627 workType "article" @default.