Supervised Machine Learning
portes grátis
Supervised Machine Learning
Optimization Framework and Applications with SAS and R
Kolosova, Tanya; Berestizhevsky, Samuel
Taylor & Francis Ltd
04/2022
182
Mole
Inglês
9780367538828
15 a 20 dias
453
Descrição não disponível.
Introduction. PART 1 1.Introduction to the AI framework. 2.Supervised Machine Learning and Its Deployment in SAS and R. 3.Bootstrap methods and Its Deployment in SAS and R. 4.Outliers Detection and Its Deployment in SAS and R. 5.Design of Experiment and Its Deployment in SAS and R. PART II 1.Introduction to the SAS and R based table-driven environment. 2.Input Data component. 3.Design of Experiment for Machine-Learning component. 4."Contaminated" Training Datasets Component. PART III 1.Insurance Industry: Underwriters decision-making process. 2.Insurance Industry: Claims Modeling and Prediction. Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
SAS Macro Program;Artificial Intelligence;Supervised Machine Learning;Bias-variance tradeoff;SID;SAS Dataset;hyper-parameters;Firth Logistic Regression;machine learning;Data Dictionary;statistical experiments;Training Datasets;optimization framework;Machine Learning Methods;Primary Key;Polynomial Kernel;SAS Macro;Data Dictionary Table;SVM Output;Bootstrap Estimate;Testing Datasets;MCD Estimate;Cox Hazard Model;MCD Method;Support Vector Machine;PROC SURVEYSELECT;Linear Mixed Model;Relational Data Model;SVM Function;SAS Data Set;SVM Method
Introduction. PART 1 1.Introduction to the AI framework. 2.Supervised Machine Learning and Its Deployment in SAS and R. 3.Bootstrap methods and Its Deployment in SAS and R. 4.Outliers Detection and Its Deployment in SAS and R. 5.Design of Experiment and Its Deployment in SAS and R. PART II 1.Introduction to the SAS and R based table-driven environment. 2.Input Data component. 3.Design of Experiment for Machine-Learning component. 4."Contaminated" Training Datasets Component. PART III 1.Insurance Industry: Underwriters decision-making process. 2.Insurance Industry: Claims Modeling and Prediction. Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
SAS Macro Program;Artificial Intelligence;Supervised Machine Learning;Bias-variance tradeoff;SID;SAS Dataset;hyper-parameters;Firth Logistic Regression;machine learning;Data Dictionary;statistical experiments;Training Datasets;optimization framework;Machine Learning Methods;Primary Key;Polynomial Kernel;SAS Macro;Data Dictionary Table;SVM Output;Bootstrap Estimate;Testing Datasets;MCD Estimate;Cox Hazard Model;MCD Method;Support Vector Machine;PROC SURVEYSELECT;Linear Mixed Model;Relational Data Model;SVM Function;SAS Data Set;SVM Method
