Search Results - (( associative classification issues algorithm ) OR ( java implication bees algorithm ))

An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm by Arkok, Bassam, Zeki, Akram M., Othman, Roslina, Aborujilah, Abdulaziz

“…Overall, this paper highlights the importance of Quranic text classification and the challenges associated with it. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm based on association function by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Zalmiyah, Zakaria, Sutikno, Tole

“…The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. …”
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Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback by Abubacker, Nirase Fathima, Azman, Azreen, Doraisamy, Shyamala, Azmi Murad, Masrah Azrifah

“…Several researchers have proposed the use of associative classifier that generates strong associations between features and reveals hidden relationship that can be missed by other classification algorithms. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

“…Finally, to address the related issues that would motivate researchers in their future work, an empirical study was utilized to assess the performance of several machine learning algorithms. � 2013 IEEE.…”

Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

“…Evolutionary algorithms have been extensively used to resolve problems associated with multiple and often conflicting objectives. …”
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Mental stress classification based on selected EEG channels using Correlation Coefficient of Hjorth Parameters by Hag, Ala, Fares, Al-Shargie, Handayani, Dini Oktarina Dwi, Houshyar, Asadi

“…Comparing our results with other recent algorithms that utilize the full set of EEG channels, CCHP achieved a superior classification accuracy of 81.56% using only eight EEG channels. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

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Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba by Ghulam , Mujtaba

“…These master feature vectors were fed as input to six machine learning algorithms to construct and evaluate the classification models. …”
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Realistic smile expression recognition approach using ensemble classifier with enhanced bagging by Hassen, Oday Ali, Abu, Nur Azman, Zainal Abidin, Zaheera, M. Darwish, Saad

“…Our model takes advantage of the intrinsic association between face detection, smile, and other face features to alleviate the over-fitting issue on the limited training set and increase classification results. …”
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Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issue... by Abdulsahib A.A., Mahmoud M.A., Mohammed M.A., Rasheed H.H., Mostafa S.A., Maashi M.S.

Random Undersampling on Imbalance Time Series Data for Anomaly Detection by Saripuddin M., Suliman A., Syarmila Sameon S., Jorgensen B.N.

Machine learning classification model for identifying internet addiction among university students by Tan, Hui Theng, Mun, Hou Kit, Handayani, Dini Oktarina Dwi

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Balancing data utility versus information loss in data-privacy protection using k-Anonymity by Esmeel, Thamer Khalil, Hasan, Md Munirul, Kabir, Muhammad Nomani, Ahmad, Firdaus

“…Based on the classification accuracy, the optimal values of k and c are obtained, and thus, the optimal k and c can be used for kanonymity algorithm to anonymize optimal number of columns of the dataset.…”
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A robust framework epileptic seizures classification based on lightweight structure deep convolutional neural network and wavelet decomposition by Nazanin Nemati, Saeed Meshgini, Ali Farzamnia

“…Most of the previous automated solutions are associated with challenges such as the lack of a proper signal descriptor, the existence of a large number of features and, consequently, the time-consuming analysis, which are not considering the uncertainty issue. …”
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Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM) by Iqtait, M., Mohamad, F.S., Mamat, M.

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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…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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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

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Satellite Image Segmentation Using Thresholding Technique by Khalik, Mohd Haffez

“…A major challenge for image segmentation is to segment the complex images with noise, intensity inhomogeneity, texture or multiphase structure. However the main issue in remote sensing is image classification that required determining an appropriate threshold between species in producing accurate segmentation image. …”
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Internet of Things (IoT) based activity recognition strategies in smart homes: a review by Babangida, Lawal, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

“…This technique is challenged by the nature of IoT technology and perceived data, as well as by human differences, which necessitated additional processing tasks to select significant features for the learning algorithms. In this work, we focus our review on activity recognition implementation strategies by examining various sensors and sensing technologies used to collect useful data from IoT devices, reviewing preprocessing and feature extraction techniques, as well as classification algorithms used to recognize human activities in smart homes. …”
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