Search Results - (( using selection method algorithm ) OR ( data visualization learning algorithm ))
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1
Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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2
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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3
Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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4
Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. …”
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5
Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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6
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Conference or Workshop Item -
7
Deep Reinforcement Learning For Control
Published 2021“…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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8
Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
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10
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
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11
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
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12
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
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13
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
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14
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
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15
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
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16
Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm
Published 2020“…In this paper, the Alpha Beta filter has been used to predict the indoor Temperature, illumination, and air quality and remove noise from the data. We applied a deep extreme learning machine approach to predict the user parameters. …”
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17
Fast shot boundary detection based on separable moments and support vector machine
Published 2021“…Moreover, for the proposed SBD algorithm, a comparative study is performed with state-of-the-art algorithms. …”
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18
Auto raise hand in Microsoft teams (API/Extension)
Published 2023“…To be more specific, it is regarding facial expression recognition based on deep learning. Artificial Intelligence focuses on developing intelligences of machines, by developing algorithms, machines are able to learn from data and patterns, even perform tasks that require human intelligence, such as visual perception, speech recognition, and decision-making. …”
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Final Year Project / Dissertation / Thesis -
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…These factors include identifying relevant atmospheric features contributing to rainfall, addressing missing data, and developing a significant model to predict daily rainfall intensity using appropriate machine-learning techniques. The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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20
EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…The IncFRNN algorithm updates the training set by employing a heuristic update method to maintain representative objects and eliminate rarely used objects. …”
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