Search Results - (( pattern classification methods algorithm ) OR ( data classification model algorithm ))
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The experimental results on artificial data sets and real-world data sets (from UCI Repository) show that the new method could improve both the efficiency and accuracy of pattern classification. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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3
Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The results from the artificial and real-world data sets (from UCI Repository) showed that the new method could improve both the efficiency and accuracy of pattern classification.…”
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Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach
Published 2019“…Classification analysis was initially performed on all seven classifier’s algorithms at 10-fold dross validation mode. …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…In this work, we integrate artificial immune algorithm with non-linear classification of pattern recognition and machine learning methods to solve the problem of intrusion detection in network systems. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023Subjects:Article -
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…SCG improves the learning process of ANNs by speeding up the adjustment of their internal weights, helping the network learn faster and more accurately from large data sets. This study aims to improve the classification of RF neural data patterns using SCG. …”
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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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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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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15
Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…DWT was used to analyze EEG signals at different frequency bands and statistics over the set of the wavelet coefficients were calculated to introduce the feature vector for SNS classifier. The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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Optimized feature construction methods for data summarizations of relational data
Published 2014“…The summarized data will then be fed to any classification algorithm to perform the classification task. …”
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Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…The classification process incorporated Root Mean Square (RMS) analysis for feature extraction and multilayer perceptron (MLP) neural networks for pattern recognition. …”
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The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Published 2021“…In comparison with other classification approaches reported in the recent studies, the proposed method enhanced the accuracy by 2.09% for data-1, 1.29% for data-2, 4.95% for data-3 and 5.71% for data-4, respectively. …”
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Classification of cervical cancer using random forest
Published 2022“…In this research, the cervical cancer risk classification model was used by using data mining approach which consider Decision Tree and Random Forest algorithm. …”
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Identifying diseases and diagnosis using machine learning
Published 2023“…For classify the disease classification algorithms are used. It uses are many dimensionality reduction algorithms and classification algorithms. …”
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