Search Results - (( course evaluation from algorithm ) OR ( label classification mining algorithm ))
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1
Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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2
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…In the second part of the study, a novel classification algorithm called Hessian semi-supervised ELM (HSS-ELM) is proposed to enhance the semi-supervised learning of ELM. …”
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3
Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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4
Feature Selection with Harmony Search for Classification: A Review
Published 2021“…A good classification accuracy can be achieved when the model correctly predicted the class labels. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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6
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…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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7
Predicting game-induced emotions using EEG, data mining and machine learning
Published 2024“…The 20 experiment cases’ results from subject-based experiments supported that the SVM classifer could accurately classify the 4 emotion states with a kappa value over 0.62, demonstrating the SVM-based algorithm’s capabilities in precisely determining the emotion label for each participant’s EEG features’ instance. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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9
A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer
Published 2023“…Machine learning and deep neural networks have shown promise in accurately representing and classifying sentiment, but they require large amounts of labeled data to train the models. In this context, the proposed novel strategy aims to eliminate the need for human labeling of the idiomatic lexicon and fine-tuning the classifier to handle the sentiment classification of tweets containing idiomatic expressions. …”
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Final Year Project / Dissertation / Thesis -
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart...
Published 2023“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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11
Using algorithmic taxonomy to evaluate lecturer workload
Published 2006“…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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12
Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction
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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal
Published 2006“…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Conference or Workshop Item -
15
Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal
Published 2006“…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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A PSO inspired asynchronous cooperative distributed hyper-heuristic for course timetabling problems
Published 2017“…The performances of the proposed cooperative hyper-heuristics are evaluated using the standard course timetabling benchmark problem. …”
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Design and development of elective courses recommender system (ECORS)
Published 2017“…Usability testing is conducted in system evaluation process using questionnaire adapted from Recommender systems' Quality of user experience (ResQue). …”
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Final Year Project Report / IMRAD -
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Prediction of MUET result based on KNN algorithm / Siti Fatimah Azzahra Hamrizan
Published 2021“…The study aims to explore the K-Nearest Neighbour (KNN) algorithm in solving the MUET result prediction problem, to develop a prototype of MUET result prediction based on the KNN algorithm and to evaluate the accuracy of the KNN algorithm in MUET result prediction. …”
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An artificial intelligence approach to monitor student performance and devise preventive measures
Published 2023“…This research evaluates the effectiveness of machine learning algorithms to monitor students� academic progress and informs the instructor about the students at the risk of ending up with unsatisfactory result in a course. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…Data for the study was collected from university records, and algorithm performance was tested against predefined scheduling criteria. …”
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