[PDF] Top 20 A Fuzzy Model of Support Vector Regression Machine
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A Fuzzy Model of Support Vector Regression Machine
... uncertain. A model of such a vague phenomenon might be represented as a fuzzy system equation which can be described by the fuzzy functions defined by Zadeh’s extension ... See full document
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Fuzzy Regression Analysis by Support Vector Learning Approach
... properties of learning machines, which enable them to generalize well in the unseen data, whereas the fuzzy set theory might be very useful for finding a fuzzy structure in an evaluation ... See full document
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Toward the Best Feature Model for Network Intrusion Detection Using Stepwise Regression and Support Vector Machine
... extension of the binary SVM classification ...value of k binary decision functions specified by the furthest positive ...number of one-against-all ... See full document
6
Fuzzy Weighted Support Vector Regression Using the Dual Coordinate Descent Method
... 在無監督學習領域，聚類和混合回歸問題是我們非常感興趣的問題。因此，SVR 也被推 廣到混合回歸問題。基於模糊理論，延伸出了模糊加權支持向量迴歸(Fuzzy Weighted Support Vector Regression/FWSVR)。通過將隸屬度引入懲罰項，FWSVR 可以處理混合迴歸問題，而 不是像以前那樣一對一地使用 SVR。然而，FWSVR ... See full document
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Leave-one-out Bounds for Support Vector Regression Model Selection
... number of function and gradient evaluations of the quasi-Newton ...number of function evaluations is the same as the number of SVRs ...numbers of function/gradient ...to a good ... See full document
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The Prediction and Investitive Decision Software of Stock Price with Support Vector Machine and Fuzzy Theory
... proposed fuzzy decision to improve our previous ...prediction of stock price of SVR with fuzzy decision that contrast to before only via opening quotation to regard as frame of ... See full document
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A modified support vector machine based prediction model on streamflow at the Shihmen Reservoir, Taiwan
... assign a lot of the budget to compensate for the losses caused by their failure to deliver water allocated for ...irrigation. A modified SVM-based predic- tion framework has therefore been proposed ... See full document
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Travel Time Prediction with Support Vector Regression
... one of the predictors. VII. C ONCLUSION Support vector machine and SVR have demonstrated their success in time-series analysis and statistical ...feasibility of applying SVR to ... See full document
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Simple Probabilistic Predictions for Support Vector Regression
... propose a rather simple approach to construct predictive intervals under given ...distribution of the target value depends on its input only through the predicted value, and modeling this distribution by ... See full document
16
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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Diagnosis of Severe Obstructive Sleep Apnea with Model Designed Using Genetic Algorithm and Ensemble Support Vector Machine
... is a general sleep disorder and is a significant cause of motor vehicle crashes and chronic ...severity of the respiratory events is measured by the frequency and duration of apneas and ... See full document
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Multiclass support vector classification via coding and regression
... multiresponse regression Consider the problem of multiclass classification with J classes based on d measurements of input attributes x A R d1 ...g A J ...construct a ... See full document
12
A comprehensive support vector machine binary hERG classification model based on extensive but biased end point hERG data sets
... identify a significant class of compounds that has been sparsely ...nature of imbalanced data sets often precludes the use of traditional QSAR modeling methodologies that rely on the selection ... See full document
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Revising Traditional Technological Prediction Model by Support Vector Regression Tools 周祐徹、吳泰熙
... aspect of the technical patent behaviors of enterprises, it can find out enterprises invest in the quantity of resource for the area of ...trend of technology and measure ... See full document
2
Fuzzy One-Class Support Vector Machines
... class of data from the rest of the feature ...one of the classes is characterized well, while no measurements are available for the other ...introduced a method of adapting the ... See full document
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THE WHALE ALGORITHM OPTIMIZED SUPPORT VECTOR MACHINE FOR CHANNEL QUALITY CONTROL OF GNSS VECTOR TRACKING LOOP
... variation of A vector can be utilized to search for prey ...position of each other. Therefore, we can use A with the random va- lues greater than 1 or less than -1 to force search agent ... See full document
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A Novel hybrid genetic algorithm for kernel function and parameter optimization in support vector regression
... offspring of the existing popu- lation. The proposed HGA-SVR model incorporates two well- known selection methods: roulette-wheel method and tournament ...not a chromosome can survive into the next ... See full document
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A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy
... GA-SVM model, the SVM parameters are dynamically optimized by implementing the RGA evo- lutionary process and the SVM model then performs the prediction task using these optimal ...process of GA-SVM ... See full document
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A new maximal-margin spherical-structured multi-class support vector machine
... advantage of using parameters M and C on controlling the number of support ...number of outlier support vectors (OSVs), as well as the minimum number of total support ... See full document
35
A new maximal-margin spherical-structured multi-class support vector machine
... logarithm of the op- timal model-parameters C, γ , M (to base 2), ...optimal model-parameters are in vari- ous ranges for different problems so it is critical to perform model-parameters ... See full document
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