Search Results - (( based classification methods algorithm ) OR ( parallel classification using algorithm ))
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1
Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…Whenever an area with the similar characteristic is verified in the next frame, the area will be identified and bounded with a rectangle through the object recognition algorithm of the research. Classification can be done precisely and efficiently for objects identified in the future frame. …”
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2
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Article -
3
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Thesis -
4
Design and analysis of management platform based on financial big data
Published 2023“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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5
Robust partitioning and indexing for iris biometric database based on local features
Published 2018“…Further, the scalable K-means++ algorithm is used for partitioning and classification processes, and an efficient parallel technique that divides the features groups causing the formation of two b-trees based on index keys is applied for search and retrieval. …”
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6
Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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Thesis -
7
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The approach was tested on the KDD Cup99 intrusion detection dataset and the results proved the proposed PSO-RKFLN as an accurate, reliable, and effective classification algorithm.…”
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8
Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor
Published 2017“…Wearable sensor technology is evolving in parallel with the demand for human activity monitoring applications. …”
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9
Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Instead of the conventional Grid Search (GS) and manual tuning (MT) approaches, automated tuning with metaheuristics approach (MA) have also shown to be effective in this task. Genetic Algorithm (GA) has been the dominant method and other MA being attempted recently has shown the potential of MA to perform hyperparameters tuning. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…This research proposes a new enhancement technique based on the Adaptive Histogram Equalization (AHE) method. …”
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Book Section -
12
An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…This research proposes a new enhancement technique based on the Adaptive Histogram Equalization (AHE) method. …”
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Thesis -
13
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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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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15
Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Eight benchmark datasets from UCI were used in the experiments to validate the performance of the proposed algorithms. …”
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Article -
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The forecasting of poverty using the ensemble learning classification methods
Published 2023“…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The method was developed based on the grid structure, whereby it was done to create a successful method of improving performance in classification. …”
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Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The method was developed based on the grid structure which was done to create a powerful method for classification. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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