Search Results - (( associative classification using algorithm ) OR ( using function methods algorithm ))
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Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…The fuzzy-ID3 algorithm with association function implementation (FID3-AF) is proposed as a classification technique for breast cancer detection. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…The proposed gene selection method combined the strength of both filter method and association analysis to identify a set of discriminative and informative genes. …”
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6
Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. …”
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Informative top-k class associative rule for cancer biomarker discovery on microarray data
Published 2020“…Nevertheless, more studies are needed on improving the predictability of the discovered gene biomarkers, as well as their reproducibility and interpretability, to qualify them for clinical use. This paper proposes an informative top-k class associative rule (iTCAR) method in an integrative framework for identifying candidate genes of specific cancers. iTCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological information from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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Informative top-k class associative rule for cancer biomarker discovery on microarray data
Published 2020“…Nevertheless, more studies are needed on improving the predictability of the discovered gene biomarkers, as well as their reproducibility and interpretability, to qualify them for clinical use. This paper proposes an informative top-k class associative rule ( i TCAR) method in an integrative framework for identifying candidate genes of specific cancers. i TCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological informa- tion from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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A framework for predicting oil-palm yield from climate data
Published 2006“…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. …”
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Structural steel plate damage detection using DFT spectral energy and artificial neural network
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Convolution Neural Network (CNN) using deep learning algorithm is chosen in identifying frequency of movement and execution time of housebreaking crime. …”
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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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BMI using spectral energy entropy for colour visual tasks
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Tracking and recognizing the activity of multi resident in smart home environments
Published 2017“…Also enable to foresee the patterns of everyday activities that commonly occur or not in an individual’s routine by considering the simplification and efficient method using the multi label classification framework. …”
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Intelligent fault diagnosis for broken rotor bar using wavelet packet signature analysis
Published 2016“…The fault detection and classification algorithm is carried out under the unknown dataset and the off-line testing results with 98.8% classification accuracy indicate good reliability of the proposed method in identifying broken rotor bars severity.…”
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Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…Data collection experiments yield a diverse dataset of hand gestures, including variations in speed, essential for algorithm development. The developed algorithms interpret raw IR-UWB radar sensor data and associate it with specific hand gestures, addressing the core objective of gesture recognition. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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Using fuzzy association rule mining in cancer classification
Published 2011“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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Ant colony algorithm for web page classification
Published 2008“…Ant Miner II is the used algorithm. It also propose a simple text preprocessing technique to reduce the large numbers of attributes associated with web content mining, without dealing linguistic complications. …”
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