Search Results - (( model evaluation metric algorithm ) OR ( a classification parallel algorithm ))
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…For sentiment detection, the AOADL-TC technique applies a parallel bidirectional gated recurrent unit (BiGRU) model. …”
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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Thesis -
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…This method resulted around 99% of classification rate. To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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Thesis -
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Improving Accuracy Metric with Precision and Recall Metrics for Optimizing Stochastic Classifier
Published 2011“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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Proceeding -
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Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier
Published 2011“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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Conference or Workshop Item -
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Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier
Published 2011“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects.We refer the new evaluation metric as optimized accuracy with recall-precision (OARP). …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023Conference Paper -
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Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review
Published 2018“…A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles. …”
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Efficient region of interest based metric learning for effective open world deep face
Published 2022“…To establish the effectiveness, we investigated various threshold finding strategies for five state-of-the-art face recognition algorithms for open world adaptation on different datasets.We also proposed a novel performance evaluation metric for FR algorithms on imbalanced datasets. …”
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Parallel execution of distributed SVM using MPI (CoDLib)
Published 2023“…Instead of using a single machine for parallel computing, multiple machines in a cluster are used. …”
Conference paper -
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
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Scheduling tight deadlines for scientific workflows in the cloud
Published 2018“…The results show that the PDC performs better in term of success rate metric while the DCCP algorithm has better performance in term of normalized cost metric. …”
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Thesis -
15
Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. …”
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Cross-project software defect prediction
Published 2022“…In this work, five research questions covering the classification algorithms, dataset, independent variables, performance evaluation metrics used in CPDP studies, and as well as the performance of individual machine learning classification algorithms in predicting software defects across different software projects were addressed accordingly. …”
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Classification models for higher learning scholarship award decisions
Published 2018“…Each model was evaluated using technical evaluation metric, such contingency table metrics, and accuracy, precision, and recall measures. …”
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The forecasting of poverty using the ensemble learning classification methods
Published 2023“…The results of the algorithms showed the poverty trend, which helped to determine the poverty classification. …”
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OAERP : A Better Measure than Accuracy in Discriminating a Better Solution for Stochastic Classification Training
Published 2011“…In this study, a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects was proposed. …”
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OAERP: a better measure than accuracy in discriminating a better solution for stochastic classification training
Published 2011“…In this study, a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects was proposed. …”
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