Search Results - (( pattern classification methods algorithm ) OR ( variables classification using algorithm ))
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Then a review of different methods currently available that can be used to solve clustering and classification problems is also given. …”
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HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling
Published 2018“…Moreover, we endeavor to present the first comprehensive and systematic analysis of intra-versus inter-subject variability in EEG-based emotion classification using VR and wearable EEG. …”
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…While mRMR was capable of identifying a subset of features that were highly relevant to the targeted classification variable, it still carry the weakness of capturing redundant features along with the algorithm. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. Feature selection, classification and pattern recognition methods have been used in this research. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The extraction network extracts detectors that represent pattern’s classes to be supplied to the classification network. …”
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Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm
Published 2015“…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…Classifier algorithms, namely the Support Vector Machine and K-Nearest Neighbours were used for benchmarking the performance of the Real-Valued Negative Selection Algorithms. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)
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Spectral and prosodic feature extractions for classical Arabic accents recognition among Malay speakers / Noor Jamaliah Ibrahim
Published 2021“…The variability of speech patterns produced by individuals is unique. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. …”
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Feature detector-level fusion methods in food recognition
Published 2019“…An automatic dietary pattern assessment via food recognition algorithm provide an alternative way to improve the overall quality of dietary pattern assessment. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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