Pattern Classification
Fluctuation Analyses for Pattern Classification in Nondestructive Materials Inspection
... series can yield relevant features for pattern classification. Such fluctuation measures, which are sometimes referred to as “fractal analyses”, were introduced in the study of mathematical fractals, ...
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PATTERN CLASSIFICATION TECHNIQUES FOR THE CLASSIFICATION OF CUTANEOUS MANIFESTATIONS OF SYSTEMIC LUPUS ERYTHEMATOSUS
... Systemic Lupus Erythematosus-lupus (SLE-Lupus) is the prototype of multiorgan autoimmune rheumatic disorders with life threatening systemic manifestations and there is no gold standard test for the diagnosis of SLE. ...
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Distance-based features in pattern classification
... of classification accuracy and/or errors, ...different pattern classification problems and the distance- based features and the original features are concatenated for another new feature ...
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Hierarchical Clustering Algorithm for Improved Incomplete Pattern Classification
... Information might be incomplete. This study proposes a classification for fragmented information. Classifying the information with missing values is a repetitive task and the outcome of the procedure relies on the ...
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On the capabilities of pattern classification using a PID concept
... In this paper we proposed a PID concept to give further information that can be used for the decision making in pattern classification tasks. The concept has been targeted to the special clustering problem, ...
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Review of EEG-based pattern classification frameworks for dyslexia
... The most important step in the analysis phase is the extraction of features. Feature extraction is transform- ing the input data into a set of features [34]. This helps to analyse the data in terms of a reduced set of ...
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Speech fundamental period estimation using pattern classification
... As previously pointed out, there are two distinct phases o f operation of pattern classifiers (including neural networks). There is the learning phase, during which the connection strengths are estimated. ...
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A Technique for Incomplete Pattern Classification by Using EM Clustering
... a pattern recognition context to calculate its ...of classification outcome, with these two k-nearest neighbors as well as with support vector machines ...
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A Survey on Various Incomplete Pattern Classification Method
... Assorted classification systems are open in writing to manage the classification of incomplete ...the classification of incomplete ...the classification of incomplete ...
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Survey on Interesting Pattern Classification
... Sequence classification used in several applications such as retrieval of data, genomic analysis, health informatics and so ...of classification on feature vectors, sequences don’t have explicit ...sequence ...
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Pattern classification using polynomial and linear regression
... Firenze Romania, Finansbank, ING Bank, Mind Bank, OTP Bank, Raiffeisen Bank, Romanian International Bank, San Paolo IMI Bank}, C2={Bank Post, Banca Comercială Carpatica}, C3={BCR, Banca [r] ...
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Pattern classification using principal components regression
... Firenze Romania, Citibank Romania, Emporiki Bank, HVB łiriac Bank, ING Bank, Mind Bank, OTP Bank, Piraeus Bank, Raiffeisen Bank, Romanian International Bank, San Paolo IMI Bank, Uni Cred[r] ...
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Pattern classification via unsupervised learners
... We use a standard state-merging technique to PAC-learn a class of probabilistic automata and show that by learning the distribution over outputs under the weaker L1 distance rather than [r] ...
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Analysis and Data Classification Methodology for Data Mining Pattern
... and pattern classification is used to classify each item in a set of cluster of data into one of predefined set of ...groups. Classification is a function of data mining, distributed collection in a ...
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Adaptive pattern recognition in a real world environment
... Pattern Classification = Local Representations Pattern Recall = Distributed Representation Exhibit 1.1 There is a one to one correspondence between the way information is represented in [r] ...
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Classification of Incomplete Pattern Using Hierarchical Clustering
... proposed Pattern classification with accomplishment used as a piece of a couple issue territories, as biometric affirmation, record classification or ...
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Improved Classification of Incomplete Pattern Using Hierarchical Clustering
... missing pattern classification for incomplete challenge activity that registers a regard and pattern by number juggling formula conviction ...incomplete pattern is ...a classification, ...
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Implementation of Prototype Based Credal Classification approach For Enhanced Classification of Incomplete Pattern
... missing pattern classification for incomplete protest operation that registers an esteem and pattern by number juggling recipe conviction ...incomplete pattern is ...a classification, ...
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Brain response pattern identification of fMRI data using a particle swarm optimization-based approach
... multi-voxel pattern analysis (MVPA) of fMRI data becomes a relatively effective approach using machine learning techniques in the recent ...multi-objective pattern classification problem with the aim ...
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Implementation of Hierarchical Clustering for Improved Classification of Incomplete Pattern
... missing pattern classification for incomplete protest operation that registers an esteem and pattern by number juggling recipe conviction ...incomplete pattern is ...a classification, ...
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