Maximum-margin hyperplane for a two-class SVM
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
... of SVM-RFE using nine cancer microarray datasets, including four multi-class ...hard-margin SVM-RFE and SVM-RFE with a properly chosen soft-margin ...than SVM-RFE for ...
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Analytical guarantees for reduced precision fixed-point margin hyperplane classifiers
... the class it belongs ...a hyperplane and assign a predicted label ˆ y based on the relative position of the feature vector with respect to the ...a maximum margin separating hyperplane ...
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SVM with a neutral class
... neutral class, ...neutral class in a learning process, its appropri- ate use can lead to the improvement in classification accu- ...adapt two variants of Tri-Class SVM (proposed by ...
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Maximum margin hashing with supervised information
... the margin of its decision sur- face, an intrinsic idea is using the similar model as the hash ...[43], SVM is used to train hash functions, but the binary codes and hash functions are learned in two ...
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Orthogonal Maximum Margin Projection for Face Recognition
... orthogonal maximum margin projection(OMMP) which is fundamentally based on the maximum margin ...builds two adjacency graphs which can best reflect the local geometrical structure of ...
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Maximum Relative Margin and Data-Dependent Regularization
... if class-conditional densities are Gaussian, second-order statis- tics are inappropriate for many real-world data sets and thus, the classification performance of LDA is typically weaker than that of ...the ...
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MedLDA: Maximum Margin Supervised Topic Models
... propose maximum entropy discrimination latent Dirichlet allocation (MedLDA), a supervised topic model leveraging the maximum margin principle for making more effective use of side information during ...
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A New Boosting Multi class SVM Algorithm
... II. SVM OVERVIEW SVM classification is based on the idea of decision hyperplanes that determine decision boundaries in input space or high dimensional feature ...space. SVM constructs linear ...
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Approximate Maximum Margin Algorithms with Rules Controlled by the Number of Mistakes
... large margin classifiers com- pletely independent of the length of the weight ...mal hyperplane for a whole class of such algorithms in which the misclassification condition and the effective ...
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Performance Evaluation of SVM-Based Information Extraction using τ Margin Values
... on SVM Light Wrapper [17]. Two steps of this Information Extraction are training and ...the SVM model, we require start and end annotations for each class of ...annotation. SVM ...
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Idiom Type Identification with Smoothed Lexical Features and a Maximum Margin Classifier
... VNIC class as the positive class, most of the errors for the two SVM models and our Syntac- tic+Smoothed models were false negatives (they classified VNICs as ...our SVM and ...
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Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision
... special mechanism of rewards. Rewards can be viewed as the training signals that drive the model to explore the search space and to find the cor- rect structure. The explicit supervision signals can be viewed as a source ...
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Indoor Wlan Positioning Using Hybrid Svm Hyperplane Margin Clustering And Regression
... (SVM) Hyperplane Margin Clustering and Regression ...the SVM Hyperplane Margin Clustering (SVMC) to reduce the search space of the fingerprint ...
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Relevant gene subset selection: the maximum margin criterion in SVM and genetic algorithm
... Specifically, this thesis extends the classic Support Vector Machine (SVM) algorithm to present a new hill- climbing method Relevant Subset Selection Using The Maximu[r] ...
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Maximum Margin Clustering
... finding maximum mar- gin hyperplanes through ...our maximum margin clustering technique often obtains more accurate results than conventional clustering ...the margin simul- taneously on ...
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Maximum-Margin Matrix Factorization
... Low-rank approximations constrain the dimensionality of the factorization X = U V 0 . Other constraints, such as sparsity and non-negativity [4], have also been suggested for better capturing the structure in Y , and ...
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Maximum Margin Algorithms with Boolean Kernels
... the maximum margin hypothesis will overfit the ...any two examples is ...large margin by using all the structure from the examples, ...the maximum margin hypothesis directly, and ...
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Sentiment Analysis Using SVM and Maximum Entropy
... In the second step this module uses the SentiStrength lexicon [13] to tag all words present in dictionary for each document with their corresponding sentiment scores... Also it furthe[r] ...
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Constant Rate Approximate Maximum Margin Algorithms
... the maximum margin classification problem in the context of perceptron-like algorithms which, however, differ from the above mentioned variants in the sense that the learning rate varies with time in more ...
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Laplacian Maximum Margin Criterion for Image Recognition
... In real-world applications, the intrinsic structure of data is often complex, and only local or global structure is not sufficient to represent the underlying intrinsic structures. So, a reasonable approach should be the ...
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