Search Results - (( data classification using algorithm ) OR ( simulation classification mining algorithm ))
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
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Comparative analysis of danger theory variants in measuring risk level for text spam messages
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Improving Classification Accuracy of Scikit-learn Classifiers with Discrete Fuzzy Interval Values
Published 2020“…In ML, different classifiers have different performance and this depends on factor such as type of data used as input for the classification phase. …”
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Discretization of integrated moment invariants for writer identification
Published 2008“…The results disclose that the proposed discretized invariants reveal 99% accuracy of classification by using 3520 training data and 880 testing data.…”
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RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart...
Published 2023“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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The summer heat of cryptojacking season : Detecting cryptojacking using heatmap and fuzzy
Published 2022“…We utilised The Fuzzy Lattice Reasoning (FLR) classifier for classification algorithms in machine learning. This experiment utilised actual cryptojacking samples and achieved a 100 percent detection accuracy rate in simulation.…”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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Framework for mining XML format business process log data
Published 2024“…Therefore, a lot of frequent subtree mining (FSM) algorithms and methods were developed to get information from semi-structured data specifically data with hierarchical nature. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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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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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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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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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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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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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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