Matches in SemOpenAlex for { <https://semopenalex.org/work/W3215867723> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W3215867723 abstract "Machine learning is a field of artificial intelligence that allows computers to predict and model future events by making inferences from past information with mathematical and statistical operations. In this study, we used tree-based regression models, one of the machine learning methods, to determine and predict the effect of health indicators of 191 countries on the human development index (HDI) between 2014 and 2018 years. When tree-based regression models were compared according to model performance criteria, it was found that the best model was the gradient boosting model with the highest R2 = 0.9962 and the smallest RMSE = 0.0094. With the gradient boosting model, the three most important variables to HDI are; current health expenditure per capita, physicians and nurses, and midwives, respectively. By selecting the ten countries with the highest HDI values and Turkey, HDI values were estimated for 2018-2019 with a gradient boosting model. The countries for which HDI values are best predicted by the gradient boosting method are Netherlands, Sweden, Norway, Iceland, Denmark, Turkey, Ireland, Germany, Australia, and China." @default.
- W3215867723 created "2021-12-06" @default.
- W3215867723 creator A5032271774 @default.
- W3215867723 creator A5074691030 @default.
- W3215867723 date "2021-11-19" @default.
- W3215867723 modified "2023-09-28" @default.
- W3215867723 title "Prediction of Human Development Index with Health Indicators Using Tree-Based Regression Models" @default.
- W3215867723 cites W1678356000 @default.
- W3215867723 cites W2070493638 @default.
- W3215867723 cites W2159267722 @default.
- W3215867723 cites W2569214105 @default.
- W3215867723 cites W2791504809 @default.
- W3215867723 cites W2903312956 @default.
- W3215867723 cites W2922181508 @default.
- W3215867723 cites W3039200512 @default.
- W3215867723 cites W3102476541 @default.
- W3215867723 cites W3107606631 @default.
- W3215867723 doi "https://doi.org/10.37094/adyujsci.895084" @default.
- W3215867723 hasPublicationYear "2021" @default.
- W3215867723 type Work @default.
- W3215867723 sameAs 3215867723 @default.
- W3215867723 citedByCount "0" @default.
- W3215867723 crossrefType "journal-article" @default.
- W3215867723 hasAuthorship W3215867723A5032271774 @default.
- W3215867723 hasAuthorship W3215867723A5074691030 @default.
- W3215867723 hasBestOaLocation W32158677231 @default.
- W3215867723 hasConcept C105795698 @default.
- W3215867723 hasConcept C119857082 @default.
- W3215867723 hasConcept C127598652 @default.
- W3215867723 hasConcept C139945424 @default.
- W3215867723 hasConcept C149782125 @default.
- W3215867723 hasConcept C152877465 @default.
- W3215867723 hasConcept C162324750 @default.
- W3215867723 hasConcept C169258074 @default.
- W3215867723 hasConcept C2779735493 @default.
- W3215867723 hasConcept C2781089502 @default.
- W3215867723 hasConcept C2908647359 @default.
- W3215867723 hasConcept C33923547 @default.
- W3215867723 hasConcept C41008148 @default.
- W3215867723 hasConcept C46686674 @default.
- W3215867723 hasConcept C50522688 @default.
- W3215867723 hasConcept C70153297 @default.
- W3215867723 hasConcept C71924100 @default.
- W3215867723 hasConcept C83546350 @default.
- W3215867723 hasConcept C84525736 @default.
- W3215867723 hasConcept C99454951 @default.
- W3215867723 hasConceptScore W3215867723C105795698 @default.
- W3215867723 hasConceptScore W3215867723C119857082 @default.
- W3215867723 hasConceptScore W3215867723C127598652 @default.
- W3215867723 hasConceptScore W3215867723C139945424 @default.
- W3215867723 hasConceptScore W3215867723C149782125 @default.
- W3215867723 hasConceptScore W3215867723C152877465 @default.
- W3215867723 hasConceptScore W3215867723C162324750 @default.
- W3215867723 hasConceptScore W3215867723C169258074 @default.
- W3215867723 hasConceptScore W3215867723C2779735493 @default.
- W3215867723 hasConceptScore W3215867723C2781089502 @default.
- W3215867723 hasConceptScore W3215867723C2908647359 @default.
- W3215867723 hasConceptScore W3215867723C33923547 @default.
- W3215867723 hasConceptScore W3215867723C41008148 @default.
- W3215867723 hasConceptScore W3215867723C46686674 @default.
- W3215867723 hasConceptScore W3215867723C50522688 @default.
- W3215867723 hasConceptScore W3215867723C70153297 @default.
- W3215867723 hasConceptScore W3215867723C71924100 @default.
- W3215867723 hasConceptScore W3215867723C83546350 @default.
- W3215867723 hasConceptScore W3215867723C84525736 @default.
- W3215867723 hasConceptScore W3215867723C99454951 @default.
- W3215867723 hasLocation W32158677231 @default.
- W3215867723 hasLocation W32158677232 @default.
- W3215867723 hasOpenAccess W3215867723 @default.
- W3215867723 hasPrimaryLocation W32158677231 @default.
- W3215867723 hasRelatedWork W2072242069 @default.
- W3215867723 hasRelatedWork W3036633074 @default.
- W3215867723 hasRelatedWork W3100297620 @default.
- W3215867723 hasRelatedWork W4206556944 @default.
- W3215867723 hasRelatedWork W4212956667 @default.
- W3215867723 hasRelatedWork W4213395718 @default.
- W3215867723 hasRelatedWork W4287755022 @default.
- W3215867723 hasRelatedWork W4296081764 @default.
- W3215867723 hasRelatedWork W4320854072 @default.
- W3215867723 hasRelatedWork W4381383350 @default.
- W3215867723 isParatext "false" @default.
- W3215867723 isRetracted "false" @default.
- W3215867723 magId "3215867723" @default.
- W3215867723 workType "article" @default.