Search Results - (( _ distribution rate algorithm ) OR ( pre evaluation ((bayes algorithm) OR (based 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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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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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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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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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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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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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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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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Security framework based multi agent system architecture to facilitate data fetching from cloud data storage by Mohamed, Amir Mohamed Talib

“…Based on the evaluation of the post-survey, GSecaaS has been developed. …”
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Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism by Alomari M.F., Mahmoud M.A., Gharaei N., Rasool S.M., Hasan R.A.

“…The core of the algorithm utilizes a Genetic Algorithm (GA) to find the optimal position for the first evaluator by minimizing the total distance between this evaluator and all CCTV nodes, aiming for surveillance efficiency. …”

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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Effects of Different Superpixel Algorithms on Interactive Segmentations by Soo See, Chai, Luong Goh, Kok, Weng Ng, Giap, Muzaffar, Hamzah

“…In this study, five different types of superpixels ranging from watershed, density, graph, clustering and energy optimization categories are evaluated. The superpixels generated by these five algorithms will be used on two interactive image segmentation algorithms: i) Maximal Similarity based Region Merging (MSRM) and ii) Graph-Based Manifold Ranking (GBMR) with single and multiple strokes on various images from the Berkeley image dataset. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

“…Evaluation was made based on various evaluation metrics related to outlier detection and clustering quality. …”
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Effects of Different Superpixel Algorithms on Interactive Segmentations by Goh, Kok Luong, Ng, Giap Weng, Muzaffar Hamzah, Chai, Soo See

“…In this study, five different types of superpixels ranging from watershed, density, graph, clustering and energy optimization categories are evaluated. The superpixels generated by these five algorithms will be used on two interactive image segmentation algorithms: i) Maximal Similarity based Region Merging (MSRM) and ii) Graph-Based Manifold Ranking (GBMR) with single and multiple strokes on various images from the Berkeley image dataset. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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Block based low complexity iterative QR precoder structure for Massive MIMO by Mok, Li Suet

“…Meanwhile, we maximize the sum rate and also consider the restrictions on the computational complexity at the base station. In this thesis, we also study and evaluate different conventional linear pre-coding schemes as well as how they relate to optimal structure of the solution which maximize the system performances. …”
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