Search Results - (( model mitigating a algorithm ) OR ( _ classification ((bayes algorithm) OR (based algorithm)) ))

Household overspending model amongst B40, M40 and T20 using classification algorithm by Zulaiha Ali, Othman, Azuraliza, Abu Bakar, Nor Samsiah, Sani, Jamaludin, Sallim

“…It will assist the government in mitigating such problems. Availability of 4 million household expenditure records obtained from the survey conducted in 2016 by the Department of Statistics Malaysia eases the aim of this study to develop a household overspending model by using machine learning. …”
Get full text
Get full text
Get full text

Comparison of Naïve bayes classifier with back propagation neural network classifier based on f - folds feature extraction algorithm for ball bearing fault diagnostic system by Osman Mohamed Addin, Addin, Salit, Mohd Sapuan, Othman, Mohamed, Ahmed Ali, Basheer Ahmed

“…This paper is intended to compare the Naïve bayes classifier for ball bearing fault diagnostic system with the back propagation neural network based on the f-folds feature extraction algorithm. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm by Yusof, Norzihani, Rosidi, Siti Aishah Rosidi, Ibrahim, Nuzulha Khilwani Ibrahim, Ahmed Ali, Ahmed El-Mogtaba Bannga

“…From the results, the different value of accuracy for both SVM and Naïve Bayes Algorithm was 2.4%. The Naïve Bayes Algorithm displayed better result comparing to SVM. …”
Get full text
Get full text
Get full text
Get full text

A Data Mining Approach to Construct Graduates Employability Model in Malaysia by Myzatul Akmam Sapaat, Aida Mustapha, Johanna Ahmad, Khadijah Chamili, Rahamirzam Muhamad

Get full text

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

“…In this research, it was found that performance of ensemble method using hybrid classifier of Random Forest – Bayes Net model was found as the best DM classification model with an accuracy of 83.91% using the Pima Indian Diabetes Dataset (PIDD) out beating all the other classification algorithms. …”
Get full text
Get full text

Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms by Nilam Nur Amir, Sjarif, Yee, Fang Lim, NurulHuda, Mohd Firdaus Azmi, Kamalia, Kamardin, Doris Wong, Hooi Ten, Hafiza, Abas, Mubarak-Ali, Al-Fahim

“…Knowledge discovery using data mining techniques are commonly applied in bankruptcy classification and prediction. This paper presents a comparison of three different classification algorithms namely NaiveBayes (NaiveBayes classifier), Logistic Regression (Logistic classifier) and C4.5 decision tree (J48 classifier) for bankruptcy classification analysis. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

Classification of Diabetes Mellitus using Ensemble Algorithms by Noor, N.A.B.S., Elamvazuthi, I., Yahya, N.

“…The objective of this study is to perform DM classification using various machine learning algorithms. …”
Get full text
Get full text

Text classification using Naive Bayes: An experiment to conference paper by Sainin, Mohd Shamrie

“…The basic text classification technique in forum application has been discussed in Sainin (2005a) and Sainin (2005b).The paper explains about the use of the basic naïve Bayes algorithm to classify forum text me ssages into two classes namely clean and bad. …”
Get full text
Get full text
Get full text

A data mining approach to construct graduates employability model in Malaysia by Sapaat, Myzatul Akmam, Mustapha, Aida, Ahmad, Johanna, Chamili, Khadijah, Muhamad, Rahamirzam

“…The performance of Bayes algorithms are also compared against a number of tree-based algorithms. …”
Get full text
Get full text
Get full text

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

“…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). …”
Get full text
Get full text

ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

“…In this paper, a new approach for Android botnet classification based on features selection and classification algorithms is proposed. …”
Get full text
Get full text

Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
Get full text
Get full text
Get full text

Accuracy and performance analysis for classification algorithms based on biomedical datasets by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Khubrani, Mousa, Fakhreldin, Mohammoud

“…Trees based Decision Tree (ID3) algorithm, Bayesian Theorem based Hidden Naïve Bayes (HNB) algorithm. …”
Get full text
Get full text
Get full text

First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
Get full text
Get full text
Get full text

Spear- phishing attack detection using artificial intelligence by Rajkumaradevan, Sanglidevan

“…The goal is to mitigate phishing and spam threats by using advanced algorithms to detect malicious URLs and classify messages effectively. …”
Get full text
Get full text

A Naïve-Bayes classifier for damage detection in engineering materials by Addin, O., Salit, Mohd Sapuan, Mahdi Ahmad Saad, Elsadig, Othman, Mohamed

“…A method for feature subset selection has also been introduced too. The method is based on mean and maximum values of the amplitudes of waves after dividing them into folds then grouping them by a clustering algorithm (e.g. k-means algorithm). …”
Get full text
Get full text
Get full text

Analysis of Sentiment Based on Opinions from the 2019 Presidential Election by Nurul Adha Oktarini, Saputri, Misinem, ., Khoirul, Zuhri

“…The classification results on the test data demonstrated that the Naive Bayes Classifier algorithm achieved an overall accuracy of 71%. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text