Search Results - (( data distribution _ algorithm ) OR ( pre evaluation ((bayes algorithm) OR (based algorithm)) ))
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1
Case Slicing Technique for Feature Selection
Published 2004“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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2
EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method
Published 2018“…Therefore, a standardized algorithm with less supervision is desired to utilize ESL for pre-surgical evaluation. …”
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3
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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4
Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…As a comparative study, the performance of the algorithms was evaluated based on various standard metrics. …”
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5
Development of an effective clustering algorithm for older fallers
Published 2022“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. Data from the Malaysian Elders Longitudinal Research (MELoR), comprising 1411 subjects aged ≥55 years, were utilized. …”
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6
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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Final Year Project / Dissertation / Thesis -
7
Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection
Published 2024“…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. The application of GA for data dimensionality reduction from 41,140 to 20,769 features, coupled with fitness evaluation based on SVM, resulted in an observed increase in accuracy by 8.10% for SVM, 36.1% for Naïve Bayes, 7.82% for LSTM, 5.47% for DNN, and 6.25% for CNN. …”
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8
Instance matching framework for heterogeneous semantic web content over linked data environment
Published 2021“…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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9
An Automated System For Classifying Conference Papers
Published 2021“…A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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Final Year Project / Dissertation / Thesis -
10
Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem
Published 2019“…In addition, it improves the exploration and exploitation capabilities of the algorithm. The standard pre-marshalling benchmark dataset (i.e., Bortfeldt-Forster) is used to evaluate the effectiveness of the proposed algorithm. …”
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11
Uncertainty estimation for improving accuracy of non-rigid registration in cardiac images
Published 2015“…In other words, uncertainty estimation is used to evaluate the registration algorithm performance which integrates intensity-based and feature-based methods. …”
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Book Section -
12
Predictive analytics for the sentiment of malaysian place of interest using machine learning models
Published 2023“…The data was then divided into training and testing sets, and was trained using three different supervised learning algorithms, namely Support Vector Machine, Random Forest, and Naive Bayes. …”
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Undergraduates Project Papers -
13
Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet ML-ADR classifier model performance evaluation with the highest kappa statistic value of 0.991, the lowest mean absolute error value of 0.0009, weighted average precision values of 99.2 %, ROC area coverage of 100 %, the most down trip decision time of 10 ms better than the existing 20 ms for conventional ADR. …”
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14
Identifying and predicting Muslim’s community funeral funding protocols
Published 2024“…Selected Machine Learning algorithms such as Decision Tree, Random Forest, and Naïve Bayes were used to classify the people that will go through funeral poverty based on a selected dataset and a survey conducted. …”
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15
Sentiment analysis on the place of interest in Malaysia
Published 2025“…The dataset was then split into training and testing sets, and three supervised learning algorithms which are Support Vector Machine, Random Forest, and Naive Bayes were employed to evaluate the sentiment analysis models. …”
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16
A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA
Published 2023“…The steps include domain understanding, data selection, data pre-processing, data transformation, data mining/modelling and model evaluation. …”
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Final Year Project Report / IMRAD -
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Security framework based multi agent system architecture to facilitate data fetching from cloud data storage
Published 2012“…In order to evaluate our proposed security framework based on MAS architecture, a pre-survey is conducted using a questionnaire survey. …”
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18
Local and global measures for measuring performance of big data analytics process
Published 2019“…More has been written about the quality of big data, its dimensions and algorithms applied on data to solve complex problems. …”
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19
A semantic conceptualization on tagged bag-of concepts to improve accuracy for sentiment Analysis
Published 2023“…This study comprises four phases: a) data collection and pre-processing, b) concepts extraction from text data using conceptualization method, c) documents deconstruction into TBoC using Long Short- Term Memory, Convolutional Neural Network, Latent Dirichlet Allocation, Rulebased, and customized algorithms, and d) sentiment classification on multiple benchmarking datasets. …”
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20
Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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