Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285182012> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W4285182012 endingPage "115" @default.
- W4285182012 startingPage "105" @default.
- W4285182012 abstract "For years, the hedonic regression model has dominated housing price research worldwide. However, the hedonic regression model suffered from the problem of over-simplification and heterogeneity. Machine learning has become a hot method in housing price prediction in recent years. The machine learning method in predicting housing prices is more accurate and precise than the traditional methods. This paper introduced three regression methods in housing price prediction: the traditional hedonic regression model, Google AutoML and Microsoft AutoML. It reviewed the factors that affected housing prices in literature and used the dataset of the housing price in Beijing in Kaggle to study the factors affected the housing price in Beijing. The results showed that Google AutoML had the best performance in predicting housing prices in Beijing. It had the highest R square (0.820) and the least RMSE and MAE. The average housing price in a community was the most important feature that impacted housing price prediction. Number of days open for sale and geographical location ranked the second and the third most important features in predicting the housing price." @default.
- W4285182012 created "2022-07-14" @default.
- W4285182012 creator A5021781600 @default.
- W4285182012 creator A5025881868 @default.
- W4285182012 date "2022-01-01" @default.
- W4285182012 modified "2023-09-23" @default.
- W4285182012 title "Predicting Housing Price in Beijing Via Google and Microsoft AutoML" @default.
- W4285182012 cites W1482278439 @default.
- W4285182012 cites W1979249583 @default.
- W4285182012 cites W2031356564 @default.
- W4285182012 cites W2045759522 @default.
- W4285182012 cites W2051688880 @default.
- W4285182012 cites W2067141068 @default.
- W4285182012 cites W2072458142 @default.
- W4285182012 cites W2251575556 @default.
- W4285182012 cites W2275146162 @default.
- W4285182012 cites W2301940971 @default.
- W4285182012 cites W2515915273 @default.
- W4285182012 cites W2735251749 @default.
- W4285182012 cites W2743729757 @default.
- W4285182012 cites W2800938332 @default.
- W4285182012 cites W2951282667 @default.
- W4285182012 cites W3015231783 @default.
- W4285182012 cites W3045887218 @default.
- W4285182012 cites W3123765358 @default.
- W4285182012 cites W3125230369 @default.
- W4285182012 cites W3125602998 @default.
- W4285182012 cites W3211717954 @default.
- W4285182012 doi "https://doi.org/10.1007/978-981-19-0737-1_7" @default.
- W4285182012 hasPublicationYear "2022" @default.
- W4285182012 type Work @default.
- W4285182012 citedByCount "1" @default.
- W4285182012 countsByYear W42851820122022 @default.
- W4285182012 crossrefType "book-chapter" @default.
- W4285182012 hasAuthorship W4285182012A5021781600 @default.
- W4285182012 hasAuthorship W4285182012A5025881868 @default.
- W4285182012 hasConcept C105795698 @default.
- W4285182012 hasConcept C119857082 @default.
- W4285182012 hasConcept C138885662 @default.
- W4285182012 hasConcept C149782125 @default.
- W4285182012 hasConcept C152877465 @default.
- W4285182012 hasConcept C162324750 @default.
- W4285182012 hasConcept C166957645 @default.
- W4285182012 hasConcept C191935318 @default.
- W4285182012 hasConcept C205649164 @default.
- W4285182012 hasConcept C2776401178 @default.
- W4285182012 hasConcept C2778304055 @default.
- W4285182012 hasConcept C2992949716 @default.
- W4285182012 hasConcept C2994591601 @default.
- W4285182012 hasConcept C33923547 @default.
- W4285182012 hasConcept C41008148 @default.
- W4285182012 hasConcept C41895202 @default.
- W4285182012 hasConcept C83546350 @default.
- W4285182012 hasConceptScore W4285182012C105795698 @default.
- W4285182012 hasConceptScore W4285182012C119857082 @default.
- W4285182012 hasConceptScore W4285182012C138885662 @default.
- W4285182012 hasConceptScore W4285182012C149782125 @default.
- W4285182012 hasConceptScore W4285182012C152877465 @default.
- W4285182012 hasConceptScore W4285182012C162324750 @default.
- W4285182012 hasConceptScore W4285182012C166957645 @default.
- W4285182012 hasConceptScore W4285182012C191935318 @default.
- W4285182012 hasConceptScore W4285182012C205649164 @default.
- W4285182012 hasConceptScore W4285182012C2776401178 @default.
- W4285182012 hasConceptScore W4285182012C2778304055 @default.
- W4285182012 hasConceptScore W4285182012C2992949716 @default.
- W4285182012 hasConceptScore W4285182012C2994591601 @default.
- W4285182012 hasConceptScore W4285182012C33923547 @default.
- W4285182012 hasConceptScore W4285182012C41008148 @default.
- W4285182012 hasConceptScore W4285182012C41895202 @default.
- W4285182012 hasConceptScore W4285182012C83546350 @default.
- W4285182012 hasLocation W42851820121 @default.
- W4285182012 hasOpenAccess W4285182012 @default.
- W4285182012 hasPrimaryLocation W42851820121 @default.
- W4285182012 hasRelatedWork W1526762968 @default.
- W4285182012 hasRelatedWork W2119194442 @default.
- W4285182012 hasRelatedWork W2365659019 @default.
- W4285182012 hasRelatedWork W2391110018 @default.
- W4285182012 hasRelatedWork W3021457118 @default.
- W4285182012 hasRelatedWork W3121191961 @default.
- W4285182012 hasRelatedWork W3121803930 @default.
- W4285182012 hasRelatedWork W3123270061 @default.
- W4285182012 hasRelatedWork W3125075435 @default.
- W4285182012 hasRelatedWork W3143900478 @default.
- W4285182012 isParatext "false" @default.
- W4285182012 isRetracted "false" @default.
- W4285182012 workType "book-chapter" @default.