Least Squares Support Vector Machines
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Summary
Support Vector Machines Basic Methods of Least Squares Support Vector Machines Bayesian Inference for LS-SVM Models Robustness Large Scale Problems LS- sVM for Unsupervised Learning LS- SVM for Recurrent Networks and Control.
- Type
- book
- Published
- 2002-11-14
- Cited by
- 1,829
- References
- 12
- OpenAlex
- https://openalex.org/W1496317909
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:53940663
Keywords
Least squares support vector machine, Least-squares function approximation, Support vector machine, Computer science, Mathematics
References
- Least squares support vector machines and primal space estimation
- Bankruptcy prediction with least squares support vector machine classifiers
- Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines
- Financial time series prediction using least squares support vector machines within the evidence framework
- Brain tumor classification based on long echo proton MRS signals
- Benchmarking Least Squares Support Vector Machine Classifiers
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- Survival SVM: a practical scalable algorithm
- An improved support vector machine with soft decision-making boundary
- On text document classification and retrieval using self-organising maps ; Tekstidokumenttien luokittelusta ja tiedonhausta itseorganisoituvilla kartoilla
- New approaches on predictive maintenance based on an environmental perspective: the cases of wind generators and diesel engines
- A faster model selection criterion for OP-ELM and OP-KNN: Hannan-Quinn criterion
- BOOTSTRAP ENHANCED N-DIMENSIONAL DEFORMATION OF SPACE WITH ACOUSTIC RESONANCE SPECTROSCOPY
- Multi-Class Classification Methods of Cost-Conscious LS-SVM for Fault Diagnosis of Blast Furnace
- Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
- Data Transformation in Modern Petrol Engine Tune-up
- Control-oriented dynamic identification modeling of a planar SOFC stack based on genetic algorithm-least squares support vector regression
- Robust and nonparametric methods for skewed data.
- Subspace regression in reproducing kernel hilbert space
- A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM
- Logistic Regression Methods with Truncated Newton Method
- Support Vector Machine Classifier with WHM Offset for Unbalanced Data
- Ensembles of Locally Linear Models: Application to Bankruptcy Prediction
- Chapter 11 Ensembles of Regularized Least Squares Classifiers for High-Dimensional Problems
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