Search Results - (( model education system algorithm ) OR ( classification _ based algorithm ))
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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Academic Exercise -
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A data mining approach to construct graduates employability model in Malaysia
Published 2011“…This study is to construct the Graduates Employability Model using classification task in data mining. To achieve it, we use data sourced from the Tracer Study, a web-based survey system from the Ministry of Higher Education, Malaysia (MOHE) for the year 2009. …”
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Imbalanced Classification Methods for Student Grade Prediction: A Systematic Literature Review
Published 2024“…Student success is essential for improving the higher education system student outcome. One way to measure student success is by predicting students' performance based on their prior academic grades. …”
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. The collected data from LinkedIn profiles then undergoes data preprocessing. …”
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Imbalanced Classification Methods for Student Grade Prediction : A Systematic Literature Review
Published 2023“…Student success is essential for improving the higher education system student outcome. One way to measure student success is by predicting students’ performance based on their prior academic grades. …”
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VGG16-based deep learning architectures for classification of lung sounds into normal, crackles, and wheezes using Gammatonegrams
Published 2023“…Breathing sounds are a rich source of information that can assist doctors in diagnosing pulmonary diseases in a non-invasive manner. Several algorithms can be developed based on these sounds to create an automatic classification system for lung diseases. …”
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Conference or Workshop Item -
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad...
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. The classification is set to two categories: Eligible or Ineligible. …”
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Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda
Published 2006“…MMB Technique only required a small size of training data. (3) Prediction process of writing style using Multiple Linear Regression (MLR) Algorithm. MLR Algorithm applied six fixed features (based on previous research) to ensure the prediction is more standardize and feature set is more significant. (4) Test the performance agreement derived from the combination of MMB, MLR and data of language component (taken from human assessment) and compared it to human assessment for five cycles of cross-validation. …”
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Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
Published 2001“…Artificial Neural Network is one of the branches of Artificial Intelligence which is utilized for the purpose of classification and prediction based on data in hand. The purpose of the study is to develop a web-based self assessment information system that can be used to obtain a model for prediction of information technology competency among teacher trainees in teaching institutes. …”
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Deep learning-based recommendation system to address challenges in providing electronic services
Published 2026“…These results confirm the model’s robustness and suitability for real-world deployment in educational institutions.…”
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Proceeding Paper -
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Application of target detection method based on convolutional neural network in sustainable outdoor education
Published 2023“…Next, the dataset of the specific underwater target image is further constructed. The acquisition system of underwater camera information of manned submersibles is designed through the Single Shot-MultiBox Detector algorithm of deep learning. …”
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Similarity reasoning-driven evolutionary fuzzy system for monotonic-preserving models
Published 2013“…The main contribution of this thesis is to formulate the fuzzy rule selection problems to facilitate the AARS and FIS modeling as an optimization problem. An optimization tool, i.e., genetic algorithm (GA), is further implemented. …”
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An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions
Published 2025“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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From Employees to Entrepreneurs: A Qualitative Exploration of Career Transitions in Ghana
Published 2025“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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A new fuzzy criterion-referenced assessment with a fuzzy rule selection technique and a monotonicity-preserving similarity reasoning scheme
Published 2013“…Nevertheless, there are several limitations in combining FIS models and CRA, as follows. (i) It is difficult to maintain the monotonicity property of the FIS-based CRA model; (ii) it is difficult and impractical to form a complete fuzzy rule base when the number of required rules is large, and (iii) reducing fuzzy rules may cause the “tomato classification” problem. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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Case Slicing Technique for Feature Selection
Published 2004“…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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