[PDF] Top 20 On the Consistency of Multiclass Classification Methods
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On the Consistency of Multiclass Classification Methods
... defines classification calibration in the setting of multiclass classification and provides a justification, in the form of Theorem 2, for studying it: classification calibration is equivalent ... See full document
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... multicategory classification algorithm that decomposes multiclass problems into a set of bi- nary classification ...ECOC classification. Also we introduce methods to improve a standard ... See full document
6
Multiclass Classification of Brain Tumor in MR Images
... segmentation methods classified into three main types that includes manual , semi automatic and fully automatic ...segmentation methods available that includes intensity based methods, region based ... See full document
11
Multiclass Brain Tumor Classification using SVM
... After taking lower resolution image from wavelet decomposition for feature extraction,feature reduction technique is applied.The principal component analysis and independent component analysis (ICA) are two well- known ... See full document
5
Confidence Sets with Expected Sizes for Multiclass Classification
... the multiclass setting is non convex, and then minimizing it is proving to be a computational ...in classification as reflected by the popularity of methods such as Boosting (Freund and Schapire, ... See full document
28
On the Consistency of Ordinal Regression Methods
... as methods that minimize a convex surrogate of the zero-one, absolute, or squared loss ...Fisher consistency. Fisher consistency is a desirable property for surrogate loss functions and implies that ... See full document
35
Composite Multiclass Losses
... for multiclass prediction has received recent attention (Zhang, 2004; Hill and Doucet, 2007; Tewari and Bartlett, 2007; Liu, 2007; Santos-Rodr´ıguez et ...a multiclass generalisation of “admissible losses” ... See full document
52
Stable feature selection and classification algorithms for multiclass microarray data
... classification methods both in term of accuracy and sta- bility of feature selection for the multiclass ...these methods for analysis of 3 independent data set for 3 types of ...proposed ... See full document
20
A Taxonomy of Label Ranking Algorithms
... including multiclass classification, multilabel classification and hierarchical ...new methods for label ranking have been proposed in the past two or three years, such as multilayer ... See full document
9
PREDICTIVE DATA MINING FRAMEWORK FOR MEDICAL DATA
... The classification technique predicts the target class for each data ...two methods of classification. In binary classification, only two possible classes such as, ―high‖ or ―low‖ risk patient ... See full document
6
Multiclass Text Classification on Unbalanced, Sparse and Noisy Data
... discusses methods to improve the performance of text classification on data that is difficult to classify due to a large number of unbalanced classes with noisy ...neural-network-based methods with ... See full document
8
Multiclass Classification with Multi-Prototype Support Vector Machines
... alternative methods are given for this optimization problem and heuristics for the ”smart” selection of patterns in the optimization process are proposed and ...state-of-the-art methods, with respect to the ... See full document
34
Iterative ensemble feature selection for multiclass classification of imbalanced microarray data
... imbalanced multiclass microarray ...selection methods including Filter ranking, FCBF, and mRMR is compared to the IEFS framework on six gene microarray data ...on multiclass gene selection ... See full document
9
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
... a multiclass classification problem (K > 2) by solving several binary classification problems, there are much fewer studies on multiclass classification algorithms based directly on ... See full document
13
Multiclass EEG motor imagery classification with sub band common spatial patterns
... different methods have shown remarkable results for binary class EEG classification [10– 14] while for better and more control commands of real- time applications such as BCI controlled wheelchair, ... See full document
9
Power transformer dissolved gas analysis through Bayesian networks and hypothesis testing
... other methods tested with the same conditions (multiclass classification, IEC TC 10 unbalanced dataset, 80% training and 20% testing) including ratio-based DGA, discrete Bayesian network models, and ... See full document
12
Use of The American Society of Anaesthesiologists Physical Status Classification in non-trauma surgical versus trauma patients: a survey of inter-observer consistency
... updated classification: massive trauma and intracranial bleed with mass effect fall into ASA Grade 5 category (moribund patient not expected to survive without the ... See full document
5
Transcription Methods for Consistency, Volume and Efficiency
... inter-transcriber consistency study conducted in 2004 as a part of the DARPA EARS (Effective, Affordable, Reusable Speech-to-Text) program illustrates this ... See full document
6
MULTICLASS OBJECT CLASSIFICATION USING NEURAL NETWORK BASED ON WAVELET TRANSFORM
... i.) DWT: The DWT is one of the most popular technique, which adopted in multiclass object classification. Wavelet transform decomposes a signal into a setoff basis functions. These basic functions are ... See full document
6
Multiclass Support Vector Machine with New Kernel for EEG Classification
... the Multiclass SVM can be used in the classification of the EEG signals by taking into consideration the misclassification ...our Multiclass SVM using wavelet based features can well preserve the ... See full document
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