Search Results - (( process classification methods algorithm ) OR ( pattern classification learning algorithm ))
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1
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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2
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…Nowadays, there are increasingly numbers of studies on seeking ways to mine Twitter for sentiment analysis. Machine learning approach such as immune system based learning methods is an alternative way for sentiment classification.This method is centered on prominent immunological theory as computation mechanisms that emulate processes in biological immune system in achieving higher probability for pattern recognition. …”
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Conference or Workshop Item -
3
Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. …”
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4
Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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5
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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6
A New Probabilistic Output Constrained Optimization Extreme Learning Machine
Published 2023“…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”
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7
Naive Bayes-guided bat algorithm for feature selection
Published 2023“…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The proposed algorithms have been tested on a variety of datasets from the UCI machine learning repository. …”
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9
Modern fuzzy min max neural networks for pattern classification
Published 2019“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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10
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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11
Hybrid multilayered perceptron network for classification of bundle branch blocks
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Working Paper -
12
Naive bayes-guided bat algorithm for feature selection.
Published 2013“…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. …”
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13
Herbs recognition based on chemical properties using machine learning algorithm
Published 2023“…This method has demonstrated promising results in identifying herb species, and the classification method based on machine learning algorithms has proven successful in recognizing and distinguishing herb species…”
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14
Systematic review for phonocardiography classification based on machine learning
Published 2023“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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15
Financial time series predicting using machine learning algorithms
Published 2013“…In the second proposed framework, Linear Regression Line (LRL) is utilised to identify the trend patterns from historical financial time series, which is supported by ANN and SVM for classification process separately. …”
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16
Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…The hybrid method was exemplified in a binary classification between digits ‘4’ and ‘9’ from a multiple features dataset. …”
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Final Year Project / Dissertation / Thesis -
17
Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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18
A review on classifying and prioritizing user review-based software requirements
Published 2024“…Investigating the potential of emerging machine learning models and algorithms to improve classification and prioritization accuracy is crucial. …”
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19
Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network
Published 2021“…The rapid advancement in pattern recognition via the deep learning method has made it possible to develop an autonomous medical image classification system. …”
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Systematic Review for Phonocardiography Classification Based on Machine Learning
Published 2023“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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