Dimensionality Reduction in Data Science
portes grátis
Dimensionality Reduction in Data Science
Jana, Kalidas; Kumar, Nirman; Yang, Ching-Chi; Venugopal, Deepak; Garzon, Max; Deng, Lih-Yuan
Springer International Publishing AG
07/2022
265
Dura
Inglês
9783031053702
15 a 20 dias
588
Descrição não disponível.
1. What is Data Science (DS)?.- 2. Solutions to Data Science Problems.- 3. What is Dimensionality Reduction (DR)?.- 4. Conventional Statistical Approaches.- 5. Geometric Approaches.- 6. Information-theoretic Approaches.- 7. Molecular Computing Approaches.- 8. Statistical Learning Approaches.- 9. Machine Learning Approaches.- 10. Metaheuristics of DR Methods.- 11. Appendices.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Classification/Prediction;Cross-validation;Data science platforms;Data visualization;Deep learning/Backpropagation;Dimensionality reduction;Experimental control;DNA hybridization;Explainable solutions;Extreme Dimensionality reduction;Geometric methods;Independent component analysis;Information-theoretic methods;Machine learning;Molecular Methods;No-Free-Lunch (NFL) theorem;Regression methods;Supervised learning;Statistical methods;Semi/Unsupervised learning
1. What is Data Science (DS)?.- 2. Solutions to Data Science Problems.- 3. What is Dimensionality Reduction (DR)?.- 4. Conventional Statistical Approaches.- 5. Geometric Approaches.- 6. Information-theoretic Approaches.- 7. Molecular Computing Approaches.- 8. Statistical Learning Approaches.- 9. Machine Learning Approaches.- 10. Metaheuristics of DR Methods.- 11. Appendices.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Classification/Prediction;Cross-validation;Data science platforms;Data visualization;Deep learning/Backpropagation;Dimensionality reduction;Experimental control;DNA hybridization;Explainable solutions;Extreme Dimensionality reduction;Geometric methods;Independent component analysis;Information-theoretic methods;Machine learning;Molecular Methods;No-Free-Lunch (NFL) theorem;Regression methods;Supervised learning;Statistical methods;Semi/Unsupervised learning
