Search Results - (( data classification techniques algorithm ) OR ( parametric classification using algorithm ))
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1
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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2
Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…The experimental results are also thoroughly evaluated and verified via non-parametric statistical analysis. Based on the obtained experimental results, the OGC, DPSO, and VDEO frameworks achieved an average enhancement up to 24.36%, 9.38%, and 11.98% of classification accuracy, respectively. …”
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4
Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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6
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
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8
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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9
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…However, the classification algorithm cannotclassify data optimally due to the challenges in dealing with variousdata sets. …”
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10
A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data
Published 2005“…Gene Selection Plays An Important Role Prior To Tissue Classification. In This Paper, A Study On Numerous Combinations Of Gene Selection Techniques And Classification Algorithms For Classification Of Microarray Gene Expression Data Is Presented. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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12
An improved data classification framework based on fractional particle swarm optimization
Published 2019“…Hence, the proposed technique can be employed to improve the overall classification accuracy and reduce the computational time in data classification applications.…”
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13
Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…The primary objective is to determine the optimal technique for predicting relevant class labels. The paper emphasizes the significance of discretization in data preprocessing, offering a comprehensive approach that combines discretization techniques with optimization algorithms. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…The primary objective is to determine the optimal technique for predicting relevant class labels. The paper emphasizes the significance of discretization in data preprocessing, offering a comprehensive approach that combines discretization techniques with optimization algorithms. …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Published 2014“…We evaluated the models generated from seven classification algorithms with two simple data balancing techniques. …”
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Data mining techniques for transformer failure prediction model: A systematic literature review
Published 2023“…Classification (of information); Forecasting; Industrial electronics; Outages; Power transformers; Preventive maintenance; Classification algorithm; Data mining algorithm; Maintenance strategies; Performance measurements; Prediction techniques; Predictive maintenance; Systematic literature review; Transformer failure; Data mining…”
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Rule pruning techniques in the ant-miner classification algorithm and its variants: A review
Published 2018“…Rule-based classification is considered an important task of data classification.The ant-mining rule-based classification algorithm, inspired from the ant colony optimization algorithm, shows a comparable performance and outperforms in some application domains to the existing methods in the literature.One problem that often arises in any rule-based classification is the overfitting problem. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…Presently, the classification accuracy of the assessment is proportional to the size of the data. …”
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20
Nearest neighbour group-based classification
Published 2010“…The results show that, while no one algorithm clearly outperforms all others on all data sets, the proposed group-based classification techniques have the potential to outperform the individual-based techniques, especially as the (group) size of the test set increases. …”
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