Search Results - (( data selection method algorithm ) OR ( new evaluation method algorithm ))
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1
Case Slicing Technique for Feature Selection
Published 2004“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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A new ant based rule extraction algorithm for web classification
Published 2011“…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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4
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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5
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. …”
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6
A combinatory algorithm of univariate and multivariate gene selection
Published 2009“…Gene selection is usually based on univariate or multivariate methods. …”
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…It utilizes the concept of classical gradient descent method with modification on the gradient selection. …”
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The new efficient and accurate attribute-oriented clustering algorithms for categorical data
Published 2012“…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
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9
A novel framework for identifying twitter spam data using machine learning algorithms
Published 2020“…Previous studies have approached spam detection as a classification problem, high dimension, time-consuming problem, which requires new methods to address the problems. This study introduces a novel framework for identifying Twitter spam data based on machine learning algorithms. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…As for EMG feature selection, the proposed algorithms are evaluated using the EMG data acquired from the publicly access EMG database. …”
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Robust generalized multiplicative scatter correction algorithm on pretreatment of near infrared spectral data
Published 2018“…In this paper, several different classical pretreatment methods were evaluated and a new robust Generalized Multiplicative Scatter Correction (GMSC) algorithm was proposed to correct the additive and/or multiplicative baseline effects in the spectral data. …”
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Feature selection methods application towards a new dataset based on online student activities / Muhammad Hareez Mohd Zaki ... [et al.]
Published 2023“…This study will perform Analysis of Variance Test (ANOVA), Chisquared Test, Recursive Feature Elimination (RFE) and Extra Tree algorithm (ET) as feature selection methods to pre-process the proposed dataset that is considered raw data. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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15
Hybrid binary whale with harris hawks for feature selection
Published 2022“…With the new hybrid feature selection method, the WOA algorithmâ��s efficiency was improved. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…Six Y-STR data sets were used as a benchmark to evaluate the performances of the algorithm against the other eight partitional clustering algorithms. …”
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions
Published 2025“…Recommended solutions to the mentioned issues are also explored. A new taxonomy for the CH-selection methods based on the technique used is proposed, along with a comparative review of other CH-selection surveys. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…The DPA-EHD is further modified by utilizing the pipelining parallelism to reduce the computing iterations and named as data parallel and pipelining algorithm (DPPA-EHD). …”
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Multiple and solid data background scheme for testing static single cell faults on SRAM memories
Published 2013“…This method is evaluated in terms of function and performance differences between the proposed MTA and existing MTA using the User Defined Algorithm (UDA) available in the MBISTArchitect tool. …”
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