Search Results - (( matrix classification problems algorithm ) OR ( java application mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm by Liu, Jingrui, Pan, Dongyang

“…A fully symmetric classification of the boundary value problem for a class of fractional differential equations with variable sequences is determined by using a fully symmetric differential sequence sorting algorithm. …”
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Facial expression type recognition using K-Nearest Neighbor algorithm / Norhafizah Saffian by Saffian, Norhafizah

“…The k-Nearest Neighbor classifier is applied as the classification algorithm. The confusion matrix calculation is used to measure the accuracy of k-NN classifier. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…The imbalanced problem of both proposed general classification algorithms which is the limitation of accuracy performance specifically in classifying on the minority class has motivated this research to improve their classification performance on imbalanced data sets. …”
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

“…With problem size of m = 5, n = 5, and 20% of nonzeroes in constraints matrix, the result of the iteration number was as follows: new augmentation algorithm = 1, QSM = 2, BLSA = 3, and Simplex = 6, and with problem size of m = 100, n = 100, and 80% of nonzeroes in constraints matrix, the result of the iteration number was as follows: new augmentation algorithm = 78, QSM = 84, BLSA = 87, and Simplex = 99. …”
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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.

Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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Document classification based on kNN algorithm by term vector space reduction by Moldagulova A., Sulaiman R.B.

A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Enhanced extreme learning machine for general regression and classification tasks by Mahmood, Saif F

“…This will allow projection to 1- norm SVM dimension in order to find the best number of nodes as support vectors. Second problem in ELM, is the restriction in performance of ELM in terms of training time and model generalization, due to the complexity of singular value decomposition (SVD) for computing the Moore-Penrose generalized inverse of the hidden layer matrix, especially on a large matrix. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Improved Artificial Neural Network Classification Model based Metaheuristic Optimization for Handwritten Character Recognition by Muhammad Arif, Mohamad, Muhammad Aliif, Ahmad

“…The problems identified specifically pertain to the classification model, particularly in the context of the Artificial Neural Network (ANN) learning problem, leading to low accuracy in recognizing handwritten characters. …”
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Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm by Taman, Ishak, Md Rosid, Nur Atika, Karis, Mohd Safirin, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Nordin, Nur Anis, Omar, Norhaizat, Jaafar, Hazriq Izzuan, Ab Ghani, Zailani, Hassan, Jefery

“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

“…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…However, in practice, high leverage points may lead to misleading results in solving variable selection problems. Therefore, a robust sure independence screening procedure based on the weighted correlation algorithm of MRFCH for high dimensional data is developed to address this problem. …”
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Personality prediction using Random Forest algorithm / Wan Abdul Qayyum Abdul Wahab by Abdul Wahab, Wan Abdul Qayyum

“…The output of this project included the project's conceptual framework, system architecture, user interface, and performance assessment, such as the confusion matrix and accuracy computation. The conclusion emphasized the findings' relevance in improving knowledge of personality prediction and classification systems, as well as future project upgrade ideas.…”
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A review on classifying and prioritizing user review-based software requirements by Salleh, Amran, Said, Mar Yah, Osman, Mohd Hafeez, Hassan, Sa’Adah

“…Investigating the potential of emerging machine learning models and algorithms to improve classification and prioritization accuracy is crucial. …”
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