Autore	Taylor Greg
Pubbl/distr/stampa	MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica	1 online resource (108 p.)
Soggetto topico	Pharmaceutical chemistry and technology
Soggetto non controllato	actuarial claim watching classification and regression trees gradient boosting granular models individual claims reserving individual models loss reserving machine learning n/a neural networks payments per claim incurred predictive modeling risk pricing
ISBN	3-03928-665-X
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Altri titoli varianti	Claim Models
Record Nr.	UNINA-9910404090203321

Autore	Attewell Paul A. <1949->
Pubbl/distr/stampa	Oakland, California : , : University of California Press, , 2015
Descrizione fisica	1 online resource (265 p.)
Disciplina	006.3/12
Soggetto topico	Social sciences - Data processing Social sciences - Statistical methods Data mining
Soggetto non controllato	analyzing data bayesian networks big data bootstrapping business analytics chaid classification and regression trees classification trees confusion matrix data analysis data mining data processing data scholarship data science hardware for data mining heteroscedasticity naive bayes partition trees permutation tests scholarly data social science social scientists software for data mining statistical methods statistical modeling studying data text mining vif regression weka
ISBN	0-520-28098-9 0-520-96059-9
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Front matter -- CONTENTS -- ACKNOWLEDGMENTS -- 1. WHAT IS DATA MINING? -- 2. CONTRASTS WITH THE CONVENTIONAL STATISTICAL APPROACH -- 3. SOME GENERAL STRATEGIES USED IN DATA MINING -- 4. IMPORTANT STAGES IN A DATA MINING PROJECT -- 5. PREPARING TRAINING AND TEST DATASETS -- 6. VARIABLE SELECTION TOOLS -- 7. CREATING NEW VARIABLES -- 8. EXTRACTING VARIABLES -- 9. CLASSIFIERS -- 10. CLASSIFICATION TREES -- 11. NEURAL NETWORKS -- 12. CLUSTERING -- 13. LATENT CLASS ANALYSIS AND MIXTURE MODELS -- 14. ASSOCIATION RULES -- CONCLUSION. Where Next? -- BIBLIOGRAPHY -- NOTES -- INDEX
Record Nr.	UNINA-9910788152303321

Autore	Sidorov Denis N
Pubbl/distr/stampa	Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica	1 online resource (272 p.)
Soggetto topico	History of engineering and technology
Soggetto non controllato	abnormal defects Adaptive Neuro-Fuzzy Inference System artificial intelligence blockchain blockchain technology cast-resin transformers classification classification and regression trees clustering component accident set cyber-physical systems data evolution mechanism decision tree energy internet energy management system energy router energy storage energy systems ensemble empirical mode decomposition extreme learning machine fatigue forecasting harmonic impedance harmonic impedance identification harmonic parameter harmonic responsibility hierarchical clustering high permeability renewable energy hybrid AC/DC power system hybrid interval forecasting industrial mathematics information security insulator fault forecast integrated energy system intelligent control Interfacial tension inverse problems linear regression model linearization load leveling machine learning maintenance monitoring data without phase angle MOPSO algorithm offshore wind farm optimization parameter estimation partial discharge pattern recognition photovoltaic output power forecasting power control power quality QoS index of energy flow relevance vector machine renewable energy source risk assessment rule extraction sample entropy scheduling optimization smart microgrid stochastic optimization time series forecasting traction network transformer oil parameters vacuum tank degasser Volterra equations Volterra models vulnerability wavelet packets wind power: wind speed: T-S fuzzy model: forecasting wind turbine
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910557678803321