Articoli correlati a Machine Learning Techniques for Prediction of Age:...
Machine Learning Techniques for Prediction of Age: From Eruption Status Of Permanent Teeth In Sri Lankan Children - Brossura
Sinossi
Prediction of age is a predominant facet in forensic and clinical fields. Forensic odontology is used to predict an age by using permanent teeth resistant to high temperatures and any mass disaster than other parts of the body. Age-related memory loss, memory loss associated with dementia, and the absence of official documents to verify their age are the main reasons people have no knowledge about their age. Therefore, age prediction is used in various situations, such as identification, admission purposes, employment, criminal issues and judicial punishments. The main objective of this study is to predict the age of a child using the eruption status of permanent teeth. This cross-sectional study was conducted on 3321 individuals (1681 males and 1640 females) from 7 provinces and 20 schools in Sri Lanka. Regression tree algorithms in Machine learning, namely Classification and regression trees (CART), gradient boosting (GB) classifier and extreme gradient boost (XGBoost) classifier, were used to make predictions for the age of a child. The study results provide an XGBoost machine learning classifier as the most suitable method for age prediction with higher accuracy.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per Machine Learning Techniques for Prediction of Age:...
Foto dell'editore
Machine Learning Techniques for Prediction of Age
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Brossura
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. Codice articolo 26395377493
Compra nuovo
EUR 56,93
Spedizione EUR 3,45
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: 4 disponibili
Foto dell'editore
Machine Learning Techniques for Prediction of Age
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Brossura
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 4 su 5 stelle
Condizione: New. Print on Demand. Codice articolo 401032330
Compra nuovo
EUR 55,41
Spedizione EUR 7,60
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 4 disponibili
Immagini fornite dal venditore
Machine Learning Techniques for Prediction of Age
Editore:
LAP LAMBERT Academic Publishing Apr 2022, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Prediction of age is a predominant facet in forensic and clinical fields. Forensic odontology is used to predict an age by using permanent teeth resistant to high temperatures and any mass disaster than other parts of the body. Age-related memory loss, memory loss associated with dementia, and the absence of official documents to verify their age are the main reasons people have no knowledge about their age. Therefore, age prediction is used in various situations, such as identification, admission purposes, employment, criminal issues and judicial punishments. The main objective of this study is to predict the age of a child using the eruption status of permanent teeth. This cross-sectional study was conducted on 3321 individuals (1681 males and 1640 females) from 7 provinces and 20 schools in Sri Lanka. Regression tree algorithms in Machine learning, namely Classification and regression trees (CART), gradient boosting (GB) classifier and extreme gradient boost (XGBoost) classifier, were used to make predictions for the age of a child. The study results provide an XGBoost machine learning classifier as the most suitable method for age prediction with higher accuracy. 80 pp. Englisch. Codice articolo 9786200311023
Compra nuovo
EUR 43,90
Spedizione EUR 23,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili
Foto dell'editore
Machine Learning Techniques for Prediction of Age
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Brossura
Da: Biblios, Frankfurt am main, HESSE, Germania
Valutazione del venditore 4 su 5 stelle
Condizione: New. PRINT ON DEMAND. Codice articolo 18395377503
Compra nuovo
EUR 57,25
Spedizione EUR 9,95
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 4 disponibili
Immagini fornite dal venditore
Machine Learning Techniques for Prediction of Age
Editore:
LAP Lambert Academic Publishing, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Brossura
Da: moluna, Greven, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Prediction of age is a predominant facet in forensic and clinical fields. Forensic odontology is used to predict an age by using permanent teeth resistant to high temperatures and any mass disaster than other parts of the body. Age-related memory loss, memo. Codice articolo 593980924
Compra nuovo
EUR 37,23
Spedizione EUR 48,99
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Machine Learning Techniques for Prediction of Age
Editore:
LAP LAMBERT Academic Publishing Apr 2022, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Prediction of age is a predominant facet in forensic and clinical fields. Forensic odontology is used to predict an age by using permanent teeth resistant to high temperatures and any mass disaster than other parts of the body. Age-related memory loss, memory loss associated with dementia, and the absence of official documents to verify their age are the main reasons people have no knowledge about their age. Therefore, age prediction is used in various situations, such as identification, admission purposes, employment, criminal issues and judicial punishments. The main objective of this study is to predict the age of a child using the eruption status of permanent teeth. This cross-sectional study was conducted on 3321 individuals (1681 males and 1640 females) from 7 provinces and 20 schools in Sri Lanka. Regression tree algorithms in Machine learning, namely Classification and regression trees (CART), gradient boosting (GB) classifier and extreme gradient boost (XGBoost) classifier, were used to make predictions for the age of a child. The study results provide an XGBoost machine learning classifier as the most suitable method for age prediction with higher accuracy.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch. Codice articolo 9786200311023
Compra nuovo
EUR 43,90
Spedizione EUR 60,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Machine Learning Techniques for Prediction of Age : From Eruption Status Of Permanent Teeth In Sri Lankan Children
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Prediction of age is a predominant facet in forensic and clinical fields. Forensic odontology is used to predict an age by using permanent teeth resistant to high temperatures and any mass disaster than other parts of the body. Age-related memory loss, memory loss associated with dementia, and the absence of official documents to verify their age are the main reasons people have no knowledge about their age. Therefore, age prediction is used in various situations, such as identification, admission purposes, employment, criminal issues and judicial punishments. The main objective of this study is to predict the age of a child using the eruption status of permanent teeth. This cross-sectional study was conducted on 3321 individuals (1681 males and 1640 females) from 7 provinces and 20 schools in Sri Lanka. Regression tree algorithms in Machine learning, namely Classification and regression trees (CART), gradient boosting (GB) classifier and extreme gradient boost (XGBoost) classifier, were used to make predictions for the age of a child. The study results provide an XGBoost machine learning classifier as the most suitable method for age prediction with higher accuracy. Codice articolo 9786200311023
Compra nuovo
EUR 44,59
Spedizione EUR 60,69
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Machine Learning Techniques for Prediction of Age | From Eruption Status Of Permanent Teeth In Sri Lankan Children
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200311021
ISBN 13: 9786200311023
Nuovo
Taschenbuch
Da: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Machine Learning Techniques for Prediction of Age | From Eruption Status Of Permanent Teeth In Sri Lankan Children | Lakshika S. Nawarathna. (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786200311023 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 121662054
Compra nuovo
EUR 39,45
Spedizione EUR 70,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 5 disponibili