Search Results - (( parameters deviations methods algorithm ) OR ( using vectorization mining algorithm ))

Document classification based on kNN algorithm by term vector space reduction by Moldagulova A., Sulaiman R.B.

Enhanced ontology-based text classification algorithm for structurally organized documents by Oleiwi, Suha Sahib

“…This research combines the ontology and text representation for classification by developing five algorithms. The first and second algorithms namely Concept Feature Vector (CFV) and Structure Feature Vector (SFV), create feature vector to represent the document. …”
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Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…Database or data warehouse is rich with hidden information that can be used to provide intelligent decision using data mining technique. …”
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Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

“…The use of data mining algorithms is expected to help in the identification of pests and diseases in chili plants. …”
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

“…This study has indicated that data mining can be a useful tool in the medical field. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”

Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

“…Support Vector Machine (SVM) is an efficient data mining approach for data classification. …”

Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

“…Face is one of the unique features of human body which has complicated characteristic.Facial features (eyes, nose, and mouth) can be used for face recognition. Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad

“…The results showed that the proposed method was efficient in identifying both the Hammerstein model subsystems in terms of the quadratic output estimation error and parameter deviation index. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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An improvement algoithm for Iris classification by using Linear Support Vector Machine (LSVM), k-Nearest Neighbours (k-NN) and Random Nearest Neighbous (RNN) / Ahmad Haadzal Kamar... by Kamarulzalis, Ahmad Haadzal, Abdullah, Mohd Asrul Affendi

“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. …”
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PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems by Mushtaq, Najeeb, Ramdan, Razali, K. G., Mohammed, Hamdan, Daniyal, Ali, M. Humada

“…The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining by Mohd Hanafi Ahmad Hijazi, Chuntao Jiang, Frans Coenen, Yalin Zheng

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Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

“…The problem lies in estimating the posterior density of the parameters which is analytically intractable. A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram, Mohammad, Othman, Faridah, Yaseen, Zaher Mundher, Afan, Haitham Abdulmohsin, Allawi, Mohammed Falah, Malek, Marlinda Abdul, Ahmed, Ali Najah, Shahid, Shamsuddin, Singh, Vijay P., El-Shafie, Ahmed

“…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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Improving sentiment reviews classification performance using support vector machine-fuzzy matching algorithm by Nurcahyawati, Vivine, Mustaffa, Zuriani

“…Many of these dimensionalities have a major impact on the complexity and performance of the algorithms used for classification. Various challenges were encountered, including how to determine the optimal combination of pre-processing techniques, how to clean the dataset, and determine the best classification algorithm. …”
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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.