Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285149112> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W4285149112 endingPage "431" @default.
- W4285149112 startingPage "419" @default.
- W4285149112 abstract "An immense career without a quality education is just a DREAM. Degree, specialization, college/University, and knowledge are key factors to achieve a great career. Career-related decisions are discussed after the 10th standard and mostly concluded after the 12th. After successful completion of 12th, the next target of any student is to get into a suitable college/university for appropriate course/program so that he can get a better education, guidance, and placement for his future. In this research, exploratory data analysis (EDA), feature selection, label encoding, feature scaling, normalization, and standardization are rigorously implemented on the dataset using various Python libraries to prepare the dataset ready to apply machine learning (ML) algorithms. We have built the ML models for the prediction of the college by a testing suite of ML classification algorithms using the K-fold cross-validation method and ensemble learning (EL) method. The suit of ML algorithms covers logistic regression, K-nearest neighbors, decision tree classifier, random forest classifier, naïve Bayes, and support vector machine classifiers. Under EL, we have tested adaptive boosting, gradient boosting, and grid search CV methods. Nevertheless, EL methods are popular and give the best performance on a predictive modeling project; we have received opposite results. After comparison, we found ML technique decision tree has higher accuracy for college prediction projects. In the end, researchers have suggested a ‘A Free guide to engineering admission aspirant parent and student (FGEAAPS)’ Web module through which engineering aspirant parents and students can take the guidance for college selection." @default.
- W4285149112 created "2022-07-14" @default.
- W4285149112 creator A5034384551 @default.
- W4285149112 creator A5052403679 @default.
- W4285149112 creator A5077980300 @default.
- W4285149112 date "2022-01-01" @default.
- W4285149112 modified "2023-09-27" @default.
- W4285149112 title "Predictive Analytics of Engineering and Technology Admissions" @default.
- W4285149112 cites W2071221659 @default.
- W4285149112 cites W2767043756 @default.
- W4285149112 cites W2801311812 @default.
- W4285149112 cites W2901668078 @default.
- W4285149112 cites W2973222509 @default.
- W4285149112 cites W2974812629 @default.
- W4285149112 cites W3138564864 @default.
- W4285149112 cites W3150635270 @default.
- W4285149112 cites W4244034953 @default.
- W4285149112 cites W4247607621 @default.
- W4285149112 doi "https://doi.org/10.1007/978-981-16-9447-9_33" @default.
- W4285149112 hasPublicationYear "2022" @default.
- W4285149112 type Work @default.
- W4285149112 citedByCount "1" @default.
- W4285149112 countsByYear W42851491122022 @default.
- W4285149112 crossrefType "book-chapter" @default.
- W4285149112 hasAuthorship W4285149112A5034384551 @default.
- W4285149112 hasAuthorship W4285149112A5052403679 @default.
- W4285149112 hasAuthorship W4285149112A5077980300 @default.
- W4285149112 hasConcept C108583219 @default.
- W4285149112 hasConcept C111919701 @default.
- W4285149112 hasConcept C119857082 @default.
- W4285149112 hasConcept C12267149 @default.
- W4285149112 hasConcept C124101348 @default.
- W4285149112 hasConcept C141404830 @default.
- W4285149112 hasConcept C148483581 @default.
- W4285149112 hasConcept C151956035 @default.
- W4285149112 hasConcept C154945302 @default.
- W4285149112 hasConcept C169258074 @default.
- W4285149112 hasConcept C188087704 @default.
- W4285149112 hasConcept C2778827112 @default.
- W4285149112 hasConcept C41008148 @default.
- W4285149112 hasConcept C46686674 @default.
- W4285149112 hasConcept C52001869 @default.
- W4285149112 hasConcept C70153297 @default.
- W4285149112 hasConcept C79158427 @default.
- W4285149112 hasConcept C83209312 @default.
- W4285149112 hasConcept C84525736 @default.
- W4285149112 hasConcept C95623464 @default.
- W4285149112 hasConceptScore W4285149112C108583219 @default.
- W4285149112 hasConceptScore W4285149112C111919701 @default.
- W4285149112 hasConceptScore W4285149112C119857082 @default.
- W4285149112 hasConceptScore W4285149112C12267149 @default.
- W4285149112 hasConceptScore W4285149112C124101348 @default.
- W4285149112 hasConceptScore W4285149112C141404830 @default.
- W4285149112 hasConceptScore W4285149112C148483581 @default.
- W4285149112 hasConceptScore W4285149112C151956035 @default.
- W4285149112 hasConceptScore W4285149112C154945302 @default.
- W4285149112 hasConceptScore W4285149112C169258074 @default.
- W4285149112 hasConceptScore W4285149112C188087704 @default.
- W4285149112 hasConceptScore W4285149112C2778827112 @default.
- W4285149112 hasConceptScore W4285149112C41008148 @default.
- W4285149112 hasConceptScore W4285149112C46686674 @default.
- W4285149112 hasConceptScore W4285149112C52001869 @default.
- W4285149112 hasConceptScore W4285149112C70153297 @default.
- W4285149112 hasConceptScore W4285149112C79158427 @default.
- W4285149112 hasConceptScore W4285149112C83209312 @default.
- W4285149112 hasConceptScore W4285149112C84525736 @default.
- W4285149112 hasConceptScore W4285149112C95623464 @default.
- W4285149112 hasLocation W42851491121 @default.
- W4285149112 hasOpenAccess W4285149112 @default.
- W4285149112 hasPrimaryLocation W42851491121 @default.
- W4285149112 hasRelatedWork W3084054221 @default.
- W4285149112 hasRelatedWork W3194296141 @default.
- W4285149112 hasRelatedWork W3204641204 @default.
- W4285149112 hasRelatedWork W4200057378 @default.
- W4285149112 hasRelatedWork W4249229055 @default.
- W4285149112 hasRelatedWork W4285149112 @default.
- W4285149112 hasRelatedWork W4293069612 @default.
- W4285149112 hasRelatedWork W4308191010 @default.
- W4285149112 hasRelatedWork W4323356248 @default.
- W4285149112 hasRelatedWork W4375930479 @default.
- W4285149112 isParatext "false" @default.
- W4285149112 isRetracted "false" @default.
- W4285149112 workType "book-chapter" @default.