Search Results - (( data classification problem algorithm ) OR ( data quality function algorithm ))

Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

“…The main objective in this study is to determine the better method to be used to find the centres in the Radial Basis Functional Link Nets for data classification. Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…For the problem of missing data, a new approach was proposed based on data partitioning and function mode. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm by Rehman Gillani, Syed Muhammad Zubair

“…The traditional Back-propagation Neural Network (BPNN) is a supervised Artificial Neural Networks (ANN) algorithm. It is widely used in solving many real time problems in world. …”
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Load balancing and server consolidation in cloud computing environments: a meta-study by Fadhil, Mohammed Alaa, Othman, Mohamed

“…Eventually, some data-center resources could come to be over-loaded/under-loaded, which leads to an increase in energy consumption in addition to decreased functioning and wastage of resources. …”
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Protein structure prediction using robust principal component analysis and support vector machine by Zakaria, Nur Aini, Ali Shah, Zuraini, Kasim, Shahreen

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A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…This thesis proposes a framework of modified adaptive neuro-fuzzy inference engine (MANFIE) for a diversity of practical applications in order to resolve the benchmark problems of a large number of inputs datasets. A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.] by Rahiman, Mohd Hezri Fazalul, Ismail, Nurlaila, Taib, Mohd Nasir, Mohd Ali, Nor Azah, Tajuddin, Saiful Nizam

“…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…When the data are induced with the lower quality model, the performance is also truncated. …”
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart... by Hamza H. M. , Altarturi

“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…Decision tree is an important method in data mining to solve the classification problems. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…The result has shown that the proposed integration system could be applied to increase the performance of the classification. However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

“…In addition, GA has the limitation on generalization which causes the problem of overfitting to the training data. Therefore a correlation-based filtering algorithm is embedded into GA feature selection to solve the over-fitting problem and increase the adaptability of the diagnostic scheme to unpredictable input data. …”
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