Search Results - (( based evaluation bayes algorithm ) OR ( level classification mining algorithm ))*

Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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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 prior result from the Matlab model of the adaptive numerical distance relay connected on midpoint integrated STATCOM power grid system indeed establish the existence of the under-reach effect for the relay zone-3 elements ing far-end short circuit fault at the coverage boundary leading to wrong impedance estimation. The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…To identify non-infected and BSR-infected trees, the WEKA tool version 3.8.5 was used for classification. The classifiers evaluated in this study were Nave Bayes (NB), Multilayer Perceptron (MLP), and Random Forest (RF). …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

“…The ZeroR algorithm was set as the baseline There are three levels of classification analyses: before and after handling the missing values, before and after the outliers’ treatment, and adding uncertain classes. …”
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri by Shukri, Ahmad Adib Baihaqi

“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Sentiment analysis of domestic violence prediction using Naive Bayes algorithm / Nurulizzah Mohd Rahiman by Mohd Rahiman, Nurulizzah

“…The research objectives focus on studying and applying the Naive Bayes algorithm for sentiment analysis on tweets related to domestic violence, aiming to provide insights for researchers, government agencies, policymakers, and the public and develop a prediction model using Naive Bayes algorithm to evaluate its performance. …”
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Prediction of college student academic performance using data mining techniques. by Abd Jalil, Azura, Mustapha, Aida, Santa, Dzulizah, Zain, Nurul Zaiha, Radwan, Rizalina

“…This study attempts to predict the success rate of students’ academic performance by analyzing their examination results to secure a place at college level for the subsequent semester. The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

“…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…In addition, level of care dataset reveals the highest accuracy of 97.15% for MLP and Bagging algorithms and the lowest accuracy of 91.66% for stacking algorithm. …”
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Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population by Abdullah, Siti Fairuz

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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…Text classification is a popular method in data mining. It is utilized to get valuable information from the vast quantity of data. …”
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Classification Analysis Of The Badminton Five Directional Lunges by Ho, Zhe Wei

“…Conclusively, the identity, game reaction time and type of lunge were found being the key determinants for badminton lunge classification accounting for highest classification accuracy in REP Tree algorithm.…”
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Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

“…Waikato Environment for Knowledge Analysis (WEKA) version 3.8 was adopted for data mining analysis at two levels of classification stages. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

“…The classification accuracy, the number of rules and the maximum length of rules obtained from the SIPIDRIP method was compared with other rough set method such as Genetic Algorithm (GA), Johnson, Holte l R, Dynamic and Exhaustive method. …”
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Comparative analysis of danger theory variants in measuring risk level for text spam messages by Zainal K., Jali M.Z., Hasan A.B.

Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

“…We propose an integrated machine learning algorithm across K-Means clustering and Naïve Bayes Classifier called KMC+NBC to overcome the aforesaid drawbacks. …”
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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

“…Regrettably, the foremost challenge of this method is to minimize false alarm while maximizing detection and accuracy rate.We propose an integrated machine learning algorithm across K-Mean s clustering and Naïve Bayes Classifier called KMC+NBC to overcome the aforesaid drawbacks.K-Means clustering is applied to labeling and gathers the entire data into corresponding cluster sets based on the data behavior,i.e.…”
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