Search Results - (( based optimization based algorithm ) OR ( learning classification modeling algorithm ))
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1
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…The optimized DBN algorithm, known as the HW-DBN algorithm, integrated through feature learning based on a Gaussian–Bernoulli Restricted Boltzmann Machine as well as classification task through a weight neuron network. …”
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Support directional shifting vector: A direction based machine learning classifier
Published 2021“…There exist several types of classification algorithms, and these are based on various bases. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The proposed framework and models that are are considered to be the specific research contributions of this thesis are: 1) a comparison framework of classification models for software defect prediction known as CF-SDP, 2) a hybrid genetic algorithm based feature selection and bagging technique for software defect prediction known as GAFS+B, 3) a hybrid particle swarm optimization based feature selection and bagging technique for software defect prediction known as PSOFS+B, and 4) a hybrid genetic algorithm based neural network parameter optimization and bagging technique for software defect prediction, known as NN-GAPO+B. …”
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10
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Predicting the classification of heart failure patients using optimized machine learning algorithms
Published 2025“…This study proposes an optimized machine learning approach using Gradient Boosting Machine (GBM) and Adaptive Inertia Weight Particle Swarm Optimization (AIWPSO) to predict heart failure survival. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This finding emphasizes that Stacking with Gradient Boosting provides much better performance in water quality classification compared to other models. This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…The major problems in classifying protein sequences into existing families/superfamilies are the following: the selection of a suitable sequence encoding method, the extraction of an optimized subset of features that possesses significant discriminatory information, and the adaptation of an appropriate learning algorithm that classifies protein sequences with higher classification accuracy. …”
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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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Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study
Published 2024“…Support Vector Machine (SVM) has become one of the traditional machine learning algorithms the most used in prediction and classification tasks. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms
Published 2021“…Proposed DM classification model is chosen based on an optimized model reflected by their accuracy and performance of the model. …”
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