Search Results - (( developing function based algorithm ) OR ( data classification model algorithm ))
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1
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…Supervised learning mainly deals with regression and classification. There exist several types of classification algorithms, and these are based on various bases. …”
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Article -
2
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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3
Jogging activity recognition using k-NN algorithm
Published 2022“…The objective of this project are 1) to investigate human activity recognition (HAR) for jogging activity and k-Nearest Neighbors (k-NN) algorithm for jogging classifier, 2) to apply HAR AND k-NN for jogging recognition and classification and, 3) to test the functionality of the k-NN algorithm of jogging recognition and classification. …”
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4
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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5
Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2021“…With that, it is very important to come out with a standard of quality classification model for agarwood oil grading’s. By continuing developing this standard, specific algorithm function has been used to make sure the ability of this model is totally not in doubt. …”
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6
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. …”
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7
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. …”
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8
Development of machine learning-based algorithm to determine the condition in transformer oil
Published 2021“…Classification learning app used to train DGA data divided into three categories fault, Not determined (N/D) and stray gassing. …”
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9
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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10
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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11
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…Rough sets theory represents a mathematical approach to vagueness and uncertainty. Data analysis, data reduction, approxi mate classification, machine learning, and discovery of pattern in data are functions performed by a rough sets analysis. …”
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12
Diagnosis and treatment recommender system for myocardial infarction using decision tree and Support Vector Machines (SVM) / Wan Marzuqiamrin Wan Mansor
Published 2025“…If the ECG image is classified as indicative of myocardial infarction, the user inputs additional patient clinical data. The decision tree algorithm functions after this point. …”
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13
A genetic algorithm based fuzzy inference system for pattern classification and rule extraction
Published 2023“…The impetus for developing a new and efficient GA-FIS model arises from the need of constructing fuzzy rules directly from raw data sets that combines good approximation and classification properties with compactness and transparency. …”
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14
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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15
Android Mobile Malware Surveillance Exploitation via Call Logs: Proof of Concept
Published 2024Conference Paper -
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Android Mobile Malware Surveillance Exploitation Via Call Logs: Proof of Concept
Published 2024“…The experiment was conducted in a controlled lab environment using open source tools by implementing dynamic analysis on 1260 datasets from the Android Malware Genome Project. Based on the experiment conducted, a new system call classification to exploit call logs for mobile attacks has been developed using Covering Algorithm. …”
Proceedings Paper -
17
EMG motion pattern classification through design and optimization of neural network
Published 2012“…Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. …”
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Proceeding Paper -
18
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…This research aims are to develop an open-source Arduino based sEMG data acquisition device by formulating hybrid automata algorithm to differentiate MUAP activity during wheelchair propulsion. …”
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19
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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20
Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…The experimental results showed that the recommended GO based models, KEGG based models, and GO-KEGG based models outperformed the expression-only models by attaining better classification accuracies with less number of genes. …”
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