Search Results - (( parameter extraction method algorithm ) OR ( data classification problem algorithm ))
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…Back Propagation (BP) has proven to be a robust algorithm for different connectionist learning problems which commonly available for any functional induction that provides a computationally efficient method. …”
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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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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In order to improve recognition of high interclass similarity activities, One-Versus- All (OVA) binarization strategy is introduced by transforming original multi-class classification problems into a series of two-class classification problems. …”
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Non-fiducial based ECG biometric authentication using one-class support vector machine
Published 2017“…Identity recognition encounters with several problems especially in feature extraction and pattern classification. …”
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar
Published 2012“…Cross validation is used to find the best parameters related to kernels used followed by training and testing of the data sets. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…Machine learning algorithms are deployed to perform sentiment classification. …”
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Computer aided diagnoses for detecting the severity of Keratoconus
Published 2024“…Methods: Data were collected from February 2022 to March 2023, comprising 97 cases from private clinics in southern Iraq. …”
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A comparative study of supervised machine learning approaches for slope failure production
Published 2023“…Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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A derivative-free optimization method for solving classification problem
Published 2010“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The result has shown that the proposed integration system could be applied to increase the performance of the classification. However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…In addition, GA has the limitation on generalization which causes the problem of overfitting to the training data. Therefore a correlation-based filtering algorithm is embedded into GA feature selection to solve the over-fitting problem and increase the adaptability of the diagnostic scheme to unpredictable input data. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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