[PDF] Top 20 Active Learning with Hinted Support Vector Machine
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Active Learning with Hinted Support Vector Machine
... for active learning, which is an important learning paradigm for reducing human labeling ...developed active learning algorithms consider both uncertainty and representative- ness when ... See full document
15
Using Support Vector Machine for Integrating Catalogs
... , ( kNN is a learning method based on similarity. Because the specific characteristics of kNN, it performs well than other learning method in text categorization problem except SVM. In recent research, kNN ... See full document
8
The Prediction and Investitive Decision Software of Stock Price with Support Vector Machine and Fuzzy Theory
... model, learning graph is more precise than original and used low support vector point even if have not bad learning efficiency and result, show in Figure ...of learning used older ... See full document
6
Online Transductive Support Vector Machine Nguyen, Thanh Tuan、陳木松
... SVM learning, in which no learning occurs when labeling unlabeled samples, the OTSVM can learn from labeled and unlabeled samples ...compare with supervised SVM learning, TSVM, PTSVM, and ... See full document
2
Travel Time Prediction with Support Vector Regression
... significantly reduces the prediction errors for the cases where there are worse prediction errors in any one of the predictors. VII. C ONCLUSION Support vector machine and SVR have demonstrated their ... See full document
6
A new maximal-margin spherical-structured multi-class support vector machine
... The support vector machine (SVM) is a very promising machine learning method proposed by Vapnik et ...compared with traditional ... See full document
35
A Newborn Screening System Based on Service-Oriented Architecture Embedded Support Vector Machine
... applications support useful mecha- nisms to simply the newborn screening daily ...data, machine learning techniques to investigate patterns for high- dimensional metabolic data are a ...The ... See full document
9
A new maximal-margin spherical-structured multi-class support vector machine
... The support vector machine (SVM) is a very promising ma- chine learning method proposed by Vapnik et ...compared with traditional ... See full document
7
Analysis of Switching Dynamics with Competing Support Vector Machines
... PLACE PHOTO HERE Chih-Jen Lin (S’91-M’98) received his B.S. degree in Mathematics from National Taiwan University in 1993. From 1995 to 1998 he studied at the Department of Industrial and Operations Engineering at the ... See full document
16
The study of sequential minimal transductive support vector machine Le Hoang Hiep、陳木松
... Support Vector Machine (SVM) is a novel machine learning algorithm based on the statistical learning ...for machine learning and data ...Transductive Support ... See full document
2
Multi-label Active Learning with Auxiliary Learner
... relevance with the support vector ...the active learning process, which decides the queries by some criterion based on the disagreement between the two ...multi-label active ... See full document
16
Optimization, Support Vector Machines, and Machine Learning
... Many other optimization issues from machine learning Need to study things useful for ML tasks.. While we complain ML people’s lack of optimization knowledge, we must admit this fact firs[r] ... See full document
121
Pornography Detection by Using Support Vector Machine
... captures and luminance that CCD sensor absorbs. Our experiment set-up is shown in Figure 3. We use LCD (Liquid Crystal Display) monitor, CCD camera, and Minolta CS-100 photometer. The experiment we do is in a dark room. ... See full document
8
PHONETIC BOUNDARY REFINEMENT USING SUPPORT VECTOR MACHINE
... 4.2. Experiment results Table 1 shows the percentage of phone boundaries correctly placed within different tolerances with respect to their as- sociated human-labeled phone boundaries. The second row represents ... See full document
4
A Fuzzy Model of Support Vector Regression Machine
... the support vector machine ...SVM learning theory characterizes properties of learning machines which enable them to generalize well and the fuzzy set theory provides an effective means ... See full document
3
A Hybrid Prototype Construction and Feature Selection Method with Parameter Optimization for Support Vector Machine
... However, these papers solely focused on data reduction, but not deal with features selection to reduce the irrelevant features for the classifier. Feature selection algorithms may be widely categorized into two ... See full document
6
Incorporating Support Vector Machine for Identifying Protein Tyrosine Sulfation Sites
... Abstract: Tyrosine sulfation is a post-translational modification of many secreted and membrane-bound proteins. It governs protein-protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine ... See full document
3
Incorporating support vector machine for identifying protein tyrosine sulfation sites
... This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider ... See full document
2
Incorporating Support Vector Machine for Identifying Protein Tyrosine Sulfation Sites
... q 2009 Wiley Periodicals, Inc. J Comput Chem 30: 2526–2537, 2009 Key words: protein; sulfation; prediction Introduction Numerous post-translational modifications (PTMs) of proteins provide the proteome with ... See full document
12
Can Support Vector Machine be a Major Classification Method ?
... Using the model selection tool (cross validation) to find out the best parameter:. /mnt/professor/cjlin/tmp%python grid.py train.[r] ... See full document
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