Search Results - (( data classification modeling algorithm ) OR ( binary classification techniques algorithm ))
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…The first objective of this study is to improve a new algorithm technique for classification. The new algorithm come from a combination of an ideas of k-NN algorithm and ensemble concept. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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An enhanced soft set data reduction using decision partition order technique
Published 2017“…In addition, the proposed decision partition order technique has reduced the choices costs and thus improves the original classification consistency. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…In this study, researcher is trying to improve the clustering of data using an efficient technique via Enhanced Binary Particle Swarm Optimization (EBPSO) as feature selection. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…The proposed method managed data and model complexity effectively while maintaining high computational efficiency. …”
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9
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM.…”
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The identification of oreochromis niloticus feeding behaviour through the integration of photoelectric sensor and logistic regression classifier
Published 2018“…It was shown that the LR model is able to yield a classification accuracy for tested data during the day at three dif- ferent time windows (4 hours each) is 100%, 88.7% and 100%, respectively, whilst the for-night data it was shown to demonstrate 100% classification accu- racy.…”
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Modelling of default risk for home credit data using machine learning approach
Published 2022“…However, with the debut and rise of financial technology, came a flood of newer modelling techniques such as machine learning. This study has as such surveyed and assessed three different modelling techniques that can be employed for credit risk analysis specifically for mortgage loan data classification. …”
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Enhanced extreme learning machine for general regression and classification tasks
Published 2020“…The method is developed for regression task by using mean/ median of ELM training errors which is then used as threshold for separating the training data and converting the continuous targets to binary. …”
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Transfer learning for sentiment analysis using bert based supervised fine-tuning
Published 2022“…As a result, we have shown a state-of-the-art binary classification performance for Bangla sentiment analysis that significantly outperforms all embedding and algorithms.…”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Vehicle classification technique for automated road traffic census
Published 2014“…This thesis proposes the development of vehicle classification technique for automated road traffic census prototype to replace manually vehicle classification by applying morphological techniques for image classification. …”
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Final Year Project Report / IMRAD -
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Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification
Published 2021“…For this purpose, the binary version of swarm algorithms facilitated with the S-shaped or sigmoid transfer function known as binary whale optimization algorithm (BWOA), binary particle swarm optimiza-tion algorithm (BPSO), and new binary manta-ray foraging opti-mization algorithm (BMRFO) are developed for feature selection. …”
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Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing
Published 2014“…This research concerns on binary classification which is classified into two classes. …”
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Automatic classification of medical x-ray images
Published 2013“…Image representation is one of the major aspects of automatic classification algorithms. In this paper, different feature extraction techniques have been utilized to represent medical X-ray images. …”
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Segmentation of Lung Region in Computed Tomography (CT) Images
Published 2015“…Segmentation of lung region in lung CT scan images is an important pre-processing technique prior automatic detection and classification of emphysema disease. …”
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Final Year Project
