Search Results - (( associative classification clustering algorithm ) OR ( java implication based algorithm ))
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…It was superior to the clustering algorithm methods in most real-world datasets with means ARI of over 0.35. …”
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3
An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…A ensemble clustering is designed, used and evaluated to generate the final classification framework that will take all input generated from the GA based clustering with Feature Selection and Feature Construction algorithms and perform the classification task for the relational datasets. …”
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4
Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…The overall performances of the three proposed frameworks have been compared with several current state-of-the-art clustering algorithms on 15 benchmark datasets from the UCI repository. …”
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5
Analysing method for acoustic emission clustering system on reinforced concrete beam
Published 2018“…The need for effective data analysis in the clustering system can be linked to three main objectives in this research; (1) to determine the type of failure on reinforced concrete beams through the AE system; (2) to identify and discriminate the AE data parameters via crack classification (tensile and shear movement); (3) to verify the crack classification of Rise Amplitude (RA) clustering by using the NI LabVIEW clustering algorithm. …”
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Frequent patterns minning of stock data using hybrid clustering association algorithm
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Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi
Published 2019“…The "Cohort study on clustering of lifestyle risk factors and understanding its association with stress on health and well-being among school teachers in Malaysia" (CLUSTer) dataset was used to compare the performance of the proposed Genetically Optimised Bayesian ARTMAP (GOBAM) model and three other classic Adaptive Resonance Theory Mapping (ARTMAP) models –Genetic Algorithm Fuzzy ARTMAP (GAFAM), Fuzzy ARTMAP (FAM), and Bayesian ARTMAP (BAM). …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…The second segmentation algorithm combines Delaunay triangulation clustering in the spatial domain and Particle Swarm Optimization (PSO). …”
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9
Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…However, numerous data mining techniques have been successfully applied in this area to find intrusions hidden in large amounts of audit data through classification, clustering or association rule. Clustering is one of the promising techniques used in Anomaly Intrusion Detection (AID), especially when dealing with unknown patterns. …”
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An improved hybrid learning approach for better anomaly detection
Published 2011“…The proposed hybrid approach will be clustering all data into the corresponding group before applying a classifier for classification purposes. …”
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11
A framework for predicting oil-palm yield from climate data
Published 2006“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. …”
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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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13
A numerical method for frequent pattern mining
Published 2009“…It plays an important role in all data mining tasks such as clustering, classification, prediction, and association analysis. …”
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Case study : an effect of noise in character recognition system using neural network
Published 2003“…These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. …”
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15
Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…On top of that, data association and algorithm modification inherit drawbacks on recognizing the residents and interactions of multi-resident complex activities. …”
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Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi
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Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks
Published 2023“…The accuracy of 2D tumor detection and segmentation are increased, enabling more 3D detection, and achieving a mean classification accuracy of 98 across system records. Finally, a hybrid approach of GoogLeNet deep learning algorithm and Convolution Neural Network- Support Vector Machines (CNN-SVM) deep learning is performed to increase the accuracy of tumor classification. …”
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A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
Published 2019“…Besides that, classification based on stroke survivors TUG score was also applied. …”
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Computational analysis of biological data: Where are we?
Published 2024“…Using computational modeling, classification algorithms can be applied to microarray and RNA sequencing data (such as hierarchical clustering - HCL, t-SNE and principal component analysis - PCA), and high-resolution images can be generated based on the analyzed data and patient samples. …”
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