Binary and Multiclass
A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data
... handle multiclass data. We validated our method on binary and mul- ticlass benchmark data sets by using both, decision trees and neural networks as base ...
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Comparison of Image Classification Techniques: Binary and Multiclass using Convolutional Neural Network and Support Vector Machines
... for binary classification whereas CNN gives consistent accuracy over binary as well as multi class classification ...for binary and multiclass ...for binary classification, to 50 % for ...
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Reducing multiclass to binary: A unifying approach for margin classifiers
... Next, we describe experiments we performed with multiclass data from the UCI repository (Merz & Murphy, 1998). We used two different popular binary learners, AdaBoost and SVM. We chose the following ...
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Stopping Criterion for Boosting Based Data Reduction Techniques: from Binary to Multiclass Problem
... So far, we have only treated binary problems. Many real-world learning problems are in fact mul- ticlass with many more possible labels. Two main strategies have been proposed to deal with this extension to ...
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Information-Theoretic Multiclass Classification Based on Binary Classifiers: On Coding Matrix Design, Reliability and Maximum Number of Classes
... the multiclass classification problem based on the direct assignment of class labels deduced from the training ...each binary classifier and to develop new soft classification rules with the increased ...
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Effective plant discrimination based on the combination of local binary pattern operators and multiclass support vector machine methods
... Local Binary Pattern (LBP) operators, for the extraction of crop leaf textural features and Support vector machine (SVM) method, for multiclass plant ...
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Enhancing Confusion Entropy (CEN) for Binary and Multiclass Classification
... general binary case is treated next, focusing on different families of matrices and carrying out the corresponding cross ...the binary setting to compare CEN with MCEN through four real database sets are ...
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Classification of Melanoma Thickness into Binary and Multiclass from Dermoscopic Images using Machine Learning Techniques
... The proposed symptomatic framework is connected on an arrangement of 289 dermoscopy pictures (114 harmful, 175 benevolent) parceled into prepare, approval, and test picture sets.[r] ...
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AdaBoost for Learning Binary and Multiclass Discriminations. (set to the music of Perl scripts) Avinash Kak Purdue University. June 8, :20 Noon
... • Note the final classification result near the bottom of the display on the previous slide. It says that the predicted class label is ’1’. It also says that the Hamming distance be- tween the binary code word ...
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Reduction from Cost-sensitive Multiclass Classification to One-versus-one Binary Classification
... the multiclass case. Thus, traditional meta-algorithms for regular multiclass classification, such as the popular one-versus-one approach, may not always work well under the cost-sensitive classification ...
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A Theory of Multiclass Boosting
... the binary conditions, they require performance that is only slightly better than random guessing, though with respect to performance measures that are more general than ordinary classification ...the ...
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Multiclass Cancer Classification by Using Fuzzy Support Vector Machine and Binary Decision Tree With Gene Selection
... of multiclass cancer classification with gene selection from gene expression ...structed multiclass classifiers with gene selection are proposed, which are fuzzy support vector machine (FSVM) with gene ...
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Lean Multiclass Crowdsourcing
... for multiclass [41] and ordinal [42] ...1 binary tasks but makes assumptions on the number of items and ...into binary tasks, but take a coding theoretic approach to estimate ...
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Composite Multiclass Losses
... The following proposition presents several characterisations of multiclass properness. It shows how the characterisation of properness in the general (not necessarily differentiable) mul- ticlass case can be ...
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Multiclass boosting with repartitioning
... A multiclass classification problem can be re- duced to a collection of binary problems with the aid of a coding ...the binary problems, is affected by both the performance of the base learner and ...
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Survey on Multiclass Classification Methods
... Figure 1: Example tree for 5-class problem Vural and Dy [20] work on a similar approach of building a binary tree of K − 1 binary classifiers, which they call Divide-By-2 (DB2). The split of classes into ...
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Measuring Monotonicity in Multiclass Classification
... in multiclass classification Abstract: Machine learning is a field in computer science where the main purpose is to create a method which can make predictions about ...data. Multiclass classification is a ...
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Blind multiclass ensemble classification
... suffers from numerical issues during the tensor whitening procedure, which explains its worst classification ER and slow runtimes. Here, the proposed approaches exhibit similar behavior to the binary case, as ...
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Multiclass learning with simplex coding
... available, multiclass learning is becoming increasingly important in ma- chine ...solving binary classification problems are well established, the problem of multicategory classification is much less ...
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Sparse Learning in Multiclass Problems.
... the binary SVM to multi-class SVM, traditional methods are to decompose a single multi-class problem into multiple independent binary problems using one-versus-one or one-versus-all ap- ...
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