Search Results - (( a distribution _ algorithm ) OR ( pre evaluation ((based algorithm) OR (bayes algorithm)) ))

Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…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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EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

“…The accuracy of ESL depends on all the stages of data processing including: head model reconstruction, signal pre-processing and inverse solution. Therefore, a standardized algorithm with less supervision is desired to utilize ESL for pre-surgical evaluation. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian by Talebian, Seyed Hamid

“…As a comparative study, the performance of the algorithms was evaluated based on various standard metrics. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

“…The DPA-EHD is further modified by utilizing the pipelining parallelism to reduce the computing iterations and named as data parallel and pipelining algorithm (DPPA-EHD). To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

“…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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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…In addition, the solutions have been evaluated based on pre-defined performance metrics and the outcomes of the optimization framework were compared with the other existing optimization techniques to evaluate the potency and the productivity of the developed MLPSO algorithm. …”

Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. …”
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A Study of Automated Essay Scoring Frameworks on Evaluating Malaysian University English Test Essays Based on Syntactic and Semantic Features by Chun Then, Lim

“…An Automated Essay Scoring (AES) system can use a trained computational model to evaluate an essay as close to the grade that a human rater would assign. …”
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An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

“…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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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

“…Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem by Mustafa, Hossam M. J., Ayob, Masri, Ahmad Nazri, Mohd Zakree, Abu-Taleb, Sawsan

“…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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Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

“…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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Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

“…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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Uncertainty estimation for improving accuracy of non-rigid registration in cardiac images by Mazaheri, Samaneh, Sulaiman, Puteri Suhaiza, Wirza, Rahmita, Dimon, Mohd Zamrin, Khalid, Fatimah, Tayebi, Rohollah Moosavi

“…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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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

“…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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Identifying and predicting Muslim’s community funeral funding protocols by Ibrahim, Izzul Ismail, M Ashhuri, Muhammad Hassan, Hassan, Raini

“…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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Sentiment analysis on the place of interest in Malaysia by Qiryn Adriana, Khairul Zaman, Wan Nur Syahidah, Wan Yusoff, Qistina Batrisyia, Azman Shah

“…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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A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA by Yeap, Ming Yue

“…The steps include domain understanding, data selection, data pre-processing, data transformation, data mining/modelling and model evaluation. …”
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A semantic conceptualization on tagged bag-of concepts to improve accuracy for sentiment Analysis by Mehanna, Yassin Samir Hassan

“…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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