Search Results - (( data classification based algorithm ) OR ( data normalization based algorithm ))

Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach by Sumiati, ., Hoga, Saragih, T.K.A, Rahman, Viktor Vekky, Ronald Repi, Agung, Triayudi

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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

“…There are two stages in the proposed classification system. Firstly, the 1D-LBP algorithm is used to extract the features of the normalized iris images and save the data in a text file according to the subject and the combinations to evaluate for the next stage. …”
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M... by Mohamad Salehuddin, Mohamad Firdaus

“…For both cases, the statistical analysis data show that the p-value is more than 0.05, which indicates that the data are normally distributed. …”
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

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Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm by Molla, M. M. Imran, Jui, Julakha Jahan, Bari, Bifta Sama, Rashid, Mamunur, Hasan, Md Jahid

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Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

“…Significant wavelengths located at visible to near infrared spectral region were used as basis for developing spectral indices to be applied onto very high resolution satellite imagery of WV-3 satellite data. The classification accuracy using spectral indices were compared with the normal supervised pixel-based classification of SVM. …”
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Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data by Mokhtari, Ahmad, Mansor, Shattri, Mahmud, Ahmad Rodzi, Mohd Shafri, Helmi Zulhaidi

“…As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
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An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

“…Many algorithms have been developed for automated electrocardiogram (ECG) classification. …”
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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms by Haw, Jia Yong, Mohd Yousof, Mohd Fairouz, Abd Rahman, Rahisham, Talib, Mohd Aizam, Azis, Norhafiz

“…However, there are times where the produce of stray gassing event might lead to fault indication in the transformer. Machine learning algorithms are used to classify the DGA data into normal condition and corresponding faults based on IEEE limits and Duval pentagon method. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…Classification approach has been widely adopted for the development of the anomaly detection model to classify the data into normal class and attack class. …”
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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

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Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

“…The selected subset of genes is then be used to train the classifiers for constructing rules for future tissue classification problem. Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

“…The optimum value of epoch and hidden nodes for each learning algorithm are determined based on the highest accuracy obtained during training phases. …”
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Risk management credit scoring prediction using sentiment analysis by Chew, Chun Phang

“…The project adopts a development-based approach with field of data science, leveraging NLP techniques and classification algorithms to seamlessly integrate sentiment-derived features with conventional credit scoring attributes. …”
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Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

“…Furthermore, Network traffic prediction algorithms based on SVM such as EaSVM have commented about the fundamental difficulties in achieving an accurate declaration that defines anomaly which suppose to solve the problem of the high rate of false positive alarm and finding excellent ways that guarantees to clear up pending issues of the network traffic normality such as the alluvial data noise of the TAaM method. …”
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