... Recently, **support** **vector** machine has received much more attention from researchers, while studies on supplier selection based on it are ...the **support** **vector** **regression** (SVR) and twin ...

13

... for **regression**, where only few labelled examples, many unlabelled instances and different data rep- resentations (multiple views) are ...extend **support** **vector** **regression** with a ...

16

... words. **Support** **Vector** Machine, **Support** **Vector** **Regression**, Sequential Minimal Opti- mization AMS subject ...The **Support** **Vector** Machine (SVM) [3] is a class of supervised ...

40

... The present work deals with the first application of **Support** **Vector** **Regression** (SVR) for the spatial data mapping. SVR is a recent development of the Statistical Learning Theory (Vapnik- Chervonenkis ...

24

... weighted **support** **vector** re- gression (SVR) model and the second is a weighted SVR-based time series ...ordinary **support** **vector** **regression** ...

21

... **Support** **vector** **regression** (SVR) and **support** **vector** classification (SVC) are popular learning tech- niques, but their use with kernels is often time ...

26

... for **support** **vector** **regression** and the pinball loss for quantile ...the **support** **vector** **regression** and the quantile regu- larized ...

18

... samples, **support** **vector** **regression** is used to forecast the tread of grain supply and ...that **support** **vector** **regression** can get good performance using some different ...

5

... February 2014 Abstract In this paper a hybrid Genetic Algorithm – **Support** **Vector** **Regression** (GA-SVR) model in economic forecasting and macroeconomic variable selection is introduced. The proposed ...

34

... Abstract. **Support** **vector** **regression** (SVR) has been a hot research topic for several years as it is an effective **regression** learning ...

12

... PENETRATION RATE OPTIMIZATION WITH **SUPPORT** **VECTOR** **REGRESSION** METHOD SUMMARY Drilling operations constitute the major part of the exploration costs. During operations, drill bits are the primary part ...

241

... Stephane.Canu@insa-rouen.fr Abstract The paper presents decision-oriented mapping of pollution using hybrid models based on statistical learning theory (**support** **vector** **regression** or SVR) and spatial ...

8

... entropy **support** **vector** **regression** (SESVR), is proposed, which is a smooth unconstrained optimization reformulation of the traditional linear programming associated with a ε-insensitive **support** ...

7

... namely **support** **vector** **regression** (SVR), to overcome the over-ﬁtting ...traditional **regression** model, the objective of SVR is to achieve the minimum structural risk rather than the minimum ...

8

... paper, **support** **vector** **regression** techniques are applied to predict loss given default of corporate bonds, where improvements are proposed to increase prediction accuracy by modifying the SVR ...

28

... to **support** plantation crops in Kabupaten ...use **Support** **Vector** **Regression** (SVR) to construct the empirical relationship in Statistical Downscaling ...

5

... Kata kunci: dasar lebar pencocokan, penyaringan topologi, dukungan regresi vektor. Abstract In this paper, we newly solve wide baseline matching using **support** **vector** **regression** (SVR). High correct ...

6

... Collaborative filtering (CF) is a popular method for the personalized recommendation. Almost all of the existing CF methods rely only on the rating data while ignoring some important implicit information in non-rating ...

11

... This paper proposes a new methodology, Sliding Window-based **Support** **Vector** **Regression** (SW-SVR), for micrometeorological data prediction. SVR is derived from a statistical learning theory and can be ...

10

... Page 52 of 56 Conclusion and Future Work This project conducts two experiments on applying feature selections with **Support** **Vector** **Regression** and feature extraction with SVR. For feature extraction ...

58