Search Results - (( mining classification using algorithm ) OR ( software classification methods algorithm ))
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Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms
Published 2018“…Knowledge discovery using data mining techniques are commonly applied in bankruptcy classification and prediction. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…The ANFIS optimized by AMBA is used employed to model classification of Malaysian small medium enterprises (SMEs) based on strength using non-financial factors. …”
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Training functional link neural network with ant lion optimizer
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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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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. …”
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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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Intuitive Content Management System to Preferences Template Throughout Data Collection by using Data Mining Classification of Prediction Method
Published 2016“…Web mining is a type of data mining which using in customer relation management (CRM). …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…In view of the needed improvement in OER, there is need to test a novel data mining, and knowledge discovery approach within collected spectrometer data from the oil palm FFB, using WEKA software for classification, and prediction of the oil palm FFB ripeness, to enhance the current manual human grader system. …”
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Classifying Indian Classical Dances By Motion Posture Patterns
Published 2019“…A total of 15 dance videos were collected from the public available domain for body joints tracking processes using the Kinovea software. Data mining analysis was performed in three stages: data pre�processing, data classification and knowledge discovery using the WEKA software. …”
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Rough Set Discretization: Equal Frequency Binning, Entropy/MDL and Semi Naives Algorithms of Intrusion Detection System
Published 2016“…Discretization of real value attributes is a vital task in data mining, particularly in the classification problem. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. …”
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Face recognition using eigenfaces and smooth support vector machine
Published 2011“…Face is one of the unique features of human body which has complicated characteristic.Facial features (eyes, nose, and mouth) can be used for face recognition. Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Undergraduates Project Papers -
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…All of these steps were conducted using Orange data mining software. Results: Based on the findings, neural network scored the highest overall accuracy of 98.6% after conducting filtering technique. …”
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Data Mining Approach To Classify Covid-19 Severity By Clinical Symptoms
Published 2021“…Missing values were treated using filtering and imputation methods. The classification algorithms: J48, SMO, Random Forest, and Simple Logistic were executed and tested to classify data into three classes: mild, moderate, and severe. …”
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Diabetes disease prediction system using HNB classifier based on discretization method
Published 2023“…Hidden Naïve Bayes is one of the algorithms for classification, which works under a data-mining model based on the assumption of conditional independence of the traditional Naïve Bayes. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…The classification is performed using the derived features from the thermal images and the backscatter features. …”
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Application of data mining techniques for economic evaluation of air pollution impact and control
Published 2007“…For that purpose, we use data mining techniques. Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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