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1
Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…In the future, different types of deep learning algorithms need to be applied, and different datasets can be tested with different hyper-parameters to produce more accurate ASD classifications.…”
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2
Applying learning to filter text
Published 2005“…Text filtering has been a successful application especially in e-mail filtering. The use of probabilistic approaches such as naïve Bayes algorithm is the effective algorithms currently known for learning to filter or classify text document.Naïve Bayes algorithm is one of the algorithms in Machine Learning that manipulates probability estimation or reasoning about the observed data.The growing of bulk e-mail or known as spam e-mail becomes a threat to users’ privacy and network load and in the case of e -mail filtering,naïve Bayes classifier can be trained to automatically detect spam messages.Similar to the e-mail, forum application may be misused by the user to send bad messages and in some extent may offence other readers.Forum filtering may be less important compared to e-mail spam filtering; however there is a possibility of using naïve Bayes to learn the messages and automatically detect bad messages.Most of the forum application found in the web is applying keyword based text filtering which scan the words and change the detected words into certain representation.Instead of defining a set of keywords to filter the forum messages, this paper will explains the experiment in applying a learning to filter text especially in the educational and anonymous forum message, where there is no user registration required to submit messages.…”
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3
Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur
Published 2007“…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
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4
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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5
A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023Conference Paper -
6
A harmony search-based learning algorithm for epileptic seizure prediction
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7
A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection
Published 2023“…The multi-agent system applies ant colony optimization and fuzzy logic search algorithms as tools to detecting learning styles. …”
Conference Paper -
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Anomaly detection in system log files using machine learning algorithms / Zahedeh Zamanian
Published 2019“…This study uses machine learning method to detect anomalies in system log files. …”
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9
A comparative analysis of predicting heart disease using machine learning algorithms
Published 2026“…This study applies six machine learning algorithms, including K-nearest neighbors, logistic regression, Bayesian classifier, decision tree, random forest, and support vector machine. …”
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10
Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques
Published 2022“…This algorithm was applied in the Python using Google Colab to make prediction of the sudden cardiac arrest. …”
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Undergraduates Project Papers -
11
Stock Price Prediction Analysis Dashboard using Machine Learning with LSTM Neural Network
Published 2021“…Machine Learning (ML) is a method of studying the computer algorithms that can improve and advance automatically throughout time with experience by using data that is collected by humans. …”
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Final Year Project -
12
Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…The SKF with opposition-based learning is also applied as adaptive beamforming algorithm for adaptive array antenna. …”
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Research Book Profile -
13
The impact of virtual reality on programming algorithm courses on student learning outcomes
Published 2024“…In the control class, students apply traditional learning, while the experimental class uses VR-based learning. …”
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14
Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
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15
Learning to Filter Text in Forum Malay Message using Naive Bayesian Technique
Published 2006“…In this Final Year Project paper, the application ofthe algorithm in the filtering forum messages will be discussed in the attempt to apply learning to filter forum messages.…”
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Final Year Project -
16
Financial trading using learning-based approach
Published 2022“…In this work, deep reinforcement learning algorithms were applied to automate the trading process. …”
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Final Year Project / Dissertation / Thesis -
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Prediction of customer churn for ABC Multistate Bank using machine learning algorithms / Hui Shan Hon ... [et al.]
Published 2023“…The purpose of this study is to apply machine learning algorithms to develop the most effective model for predicting bank customer churn. …”
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18
Fast sequential learning methods on RBF-network using decomposed training algorithms
Published 2004“…This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. …”
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Conference or Workshop Item -
19
Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…In this paper, object detection model is developed and implemented with deep learning algorithm. Object classification model is produced through the model training with Deep Neural Networks (DNN). …”
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Proceedings -
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…Annually, almost half a million women do not survive the disease and die from breast cancer. Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. …”
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