Search Results - (( knowledge utilization using algorithm ) OR ( data classification using algorithm ))

Knowledge base processing method based on text classification algorithm by Baisheng Zhong, Mohd Shamrie Sainin, Tan Soo Fun

“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…Feature selection and classification are widely utilized for data analysis. …”
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An extended ID3 decision tree algorithm for spatial data by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

“…Utilizing data mining tasks such as classification on spatial data is more complex than those on non-spatial data. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…The experiment was executed by using k-fold cross validation techniques for predicting the classification algorithm performance. …”
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Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Mohamed, Shakir, Qidwai, Uvais, Malik, Aamir Saeed, Kamel , Nidal

“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification by Ahmad, N.

“…Growing self-organizing map (GSOM) has been introduced as an improvement to the self-organizing map (SOM) algorithm in clustering and knowledge discovery. Unlike the traditional SOM, GSOM has a dynamic structure which allows nodes to grow reflecting the knowledge discovered from the input data as learning progresses. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Shakir, Mohamed, Qidwai, Uvais, Malik, Aamir Saeed, Kamel, Nidal

“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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Stress Classification using Deep Learning with 1D Convolutional Neural Networks by Abdulrazak Yahya, Saleh, Khai Xian, Lau

“…Artificial Intelligence (AI) interprets external data, learns from such data, and uses the learning to achieve specific goals and tasks. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

“…We then review the state-of-the-art US-based CAD techniques that utilize a range of image texture based features like entropy, Local Binary Pattern (LBP), Haralick textures and run length matrix in several automated decision making algorithms. These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

“…The algorithm is utilized for predicting a huge set of unlabeled data, given a small number of labelled data. …”
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Feature selection for Malaysian medicinal plant leaf shape identification and classification by Sainin, Mohd Shamrie, Alfred, Rayner

“…Malaysian medicinal plants may be abundant natural resources but there has not been much research done on preserving the knowledge of these medicinal plants which enables general public to know the leaf using computing capability.Therefore, in this preliminary study, a novel framework in order to identify and classify tropical medicinal plants in Malaysia based on the extracted patterns from the leaf is presented.The extracted patterns from medicinal plant leaf are obtained based on several angle features.However, the extracted features create quite large number of attributes (features), thus degrade the performance most of the classifiers.Thus, a feature selection is applied to leaf data and to investigate whether the performance of a classifier can be improved.Wrapper based genetic algorithm (GA) feature selection is used to select the features and the ensemble classifier called Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) is used as a classifier.The performance of the feature selection is compared with two feature selections from Weka.In the experiment, five species of Malaysian medicinal plants are identified and classified in which will be represented by using 65 images.This study is important in order to assist local community to utilize the knowledge and application of Malaysian medicinal plants for future generation.…”
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Predicting STEM academic performance in secondary schools: data mining approach by Termedi @Termiji, Mohammad Izzuan, Ab. Jalil, Habibah

“…Three different data mining classification algorithms which are Decision Tree (DT), Artificial Neural Networks (ANN), and Naive Bayes (NB) will be used on the dataset. …”
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A framework for malware identification based on behavior by Mohamad Fadli, Zolkipli

“…The IF-THEN Prediction Rules which is generated using the data mining technique, ID3 Algorithm is used. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
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Benthic habitat mapping and coral bleaching detection using quickbird imagery and Kd algorithm by Kabiri, Keivan

“…Half numbers of these points were selected to determine the mentioned parameters using minimizing the sum of the squared residuals, and the other points were used for accuracy assessment of the applied method. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…Sentiment analysis algorithms used to classify the sentiment of tweets on social media platforms such as Twitter face challenges when dealing with idiomatic expressions and figurative language used by users. …”
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Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset by Abd Rahman, M. Hafiz Fazren, Wan Salim, Wan Wardatul Amani, Abd-Wahab, Firdaus

“…This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using several well-known machine learning algorithm such as Decision Tree, Support Vector Machine and Naïve Bayers. …”
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