Search Results - (( effective classification problem algorithm ) OR ( data optimization method algorithm ))
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A derivative-free optimization method for solving classification problem
Published 2010“…There is a training set for each class. Those problems occur in a wide range of human activity. One of the most promising ways to data classification is based on methods of mathematical optimization. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The focus of this thesis is on solvingclustering and classification problems. Specifically, we will focus on new optimization methods for solving clustering and classification problems. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Thus, both proposed imbalanced LR-based methods is simple and effective for classification of imbalanced data sets and have promising results.…”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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5
Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal
Published 2017“…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Enhancement of new smooth support vector machines for classification problems
Published 2011“…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
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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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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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14
A direct ensemble classifier for imbalanced multiclass learning
Published 2012“…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A...
Published 2023“…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. …”
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Accurate and reliable diagnosis and classification using probabilistic ensemble simplified fuzzy ARTMAP
Published 2005“…For the medical diagnosis and classification problems, PESFAM achieves 100 percent in accuracy, specificity, and sensitivity based on the 10-fold crossvalidation and these results are superior to those from other classification algorithms. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…Five state-of-the-art FS methods are used to evaluate the effectiveness of proposed methods in this work. …”
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Tree-based contrast subspace mining method
Published 2020“…Genetic algorithm has been widely used to find global solution to optimization and search problem. …”
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Case study : an effect of noise in character recognition system using neural network
Published 2003“…This projects uses the most popular training method in character recognition problem, namely backpropagation algorithm. …”
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