Search Results - (( model evaluation based algorithm ) OR ( label classification bayes algorithm ))

Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad by Ahmad, Nurul Atirah

“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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Comparative analysis of text classification algorithms for automated labelling of quranic verses by Adeleke, Abdullah, Samsudin, Noor Azah, Mustapha, Aida, Mohd Nawi, Nazri

“…We applied three text classification algorithms namely, k-Nearest Neighbour, Support Vector Machine, and Naïve Bayes in automating the labelling procedure. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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A comparative study in classification techniques for unsupervised record linkage model by Ektefa, Mohammadreza, Sidi, Fatimah, Ibrahim, Hamidah, A. Jabar, Marzanah, Memar, Sara

“…In order to utilize the supervised classification algorithms without consuming a lot of time for labeling data manually, a two step method which selects the training data automatically has been proposed in previous studies. …”
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

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Sentiment analysis regarding childcare issues using Naive Bayes Algorithm / Alis Farhana Zulkipeli by Zulkipeli, Alis Farhana

“…VADER is used for initial sentiment labeling, and the Naive Bayes classifier categorizes sentiments into positive and negative classes. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
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Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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An enhanced feature selection technique for classification of group based holy Quran verses by Abdullahi Oyekunle, Adeleke

“…This thesis is about proposing an enhanced feature selection technique for text classification applications. Text classification problem is primarily applied in document labeling. …”
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An enhanced feature selection technique for classification of group-based holy quran verses by Oyekunle, Adeleke Abdullahi

“…This thesis is about proposing an enhanced feature selection technique for text classification applications. Text classification problem is primarily applied in document labeling. …”
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Sentiment Analysis of Omicron COVID-19 Variant using Naïve Bayes Classifier and RapidMiner by Dayu, Wijaya, Leon A., Abdillah

“…Then, the comments will be manually labeled followed by classification using the Nave Bayes algorithm and RapidMiner software. …”
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Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic by Jiao, BianBian, Leelavathi, R., Lohgheswary, N., Nopiah, Z. M.

“…The empirical part adopts dictionary emotion recognition method and machine learning emotion recognition respectively. The algorithms used include support vector machine and naive Bayes based on TFIDF, support vector machine and LSTM based on wod2vec. …”
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Boosting and bagging classification for computer science journal by Wibawa, Aji Prasetya, Putri, Nastiti Susetyo Fanany, Al Rasyid, Harits, Nafalski, Andrew, Hashim, Ummi Rabaah

“…Therefore, a method of categorization is provided to solve this issue. Classification is a machine-learning technique that groups data based on the supplied label class. …”
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Analyzing Algorithms to Detect Disaster Events using Social Media by Azlan F.A., Ahmad A., Yussof S., Ghapar A.A.

Fake news detection: A machine learning approach by Yeoh, Dennis Guan Lee

“…The final model chosen to be deployed was a model trained using a Multinomial Naïve Bayes algorithm.…”
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Incorporating the range-based method into GridSim for modeling task and resource heterogeneity by Eng, Kailun, Muhammed, Abdullah, Mohamed, Mohamad Afendee, Hasan, Sazlinah

“…As heterogeneity is one of the unique characteristics of Grid computing, which induces additional challenges in designing heuristic-based scheduling algorithms, the main concern when performing simulation experiments for evaluating the performance of scheduling algorithms is how to model and simulate different Grid scheduling scenarios or cases that capture the inherent nature of heterogeneity of Grid computing environment. …”
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