Search Results - (( using vector method algorithm ) OR ( pattern classification model algorithm ))
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Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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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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Thesis -
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Financial time series predicting using machine learning algorithms
Published 2013“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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Optimized feature construction methods for data summarizations of relational data
Published 2014“…The summarized data will then be fed to any classification algorithm to perform the classification task. …”
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Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach
Published 2019“…Earlier studies in the handwriting recognition field were mostly focused on recognizing characters using Neural Network Language Model (NNLM) classifier, Hidden Markov Model (HMM), and Support Vector Machine (SVM) with segmentation technique, Hough Transform method, and structural features. …”
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Monograph -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…In view of their respective strength and deficiency, this study combined both these methods and used a support vector machine (SVM) as the underlying classifier anticipating the mRMR to make an excellent complement to the SVM-RFE. …”
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Classification of cervical cancer using random forest
Published 2022“…In this research, the cervical cancer risk classification model was used by using data mining approach which consider Decision Tree and Random Forest algorithm. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Furthermore, comparative analysis with existing methods in the field highlights the CNN-LSTM-SA model's ability to address scalability, adaptability and classification challenges. …”
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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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Non-fiducial based ECG biometric authentication using one-class support vector machine
Published 2017“…The personal identity verification in a random population using kernel-based binary and one-class Support Vector Machines (SVMs) has been considered by other biometric traits, but has been so far left aside for analysis of ECG signals. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…A Convolutional Neural Network (CNN) model was created from scratch for this study. Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling
Published 2018“…This study presents the classification of emotions on EEG signals using commercial BCI headsets known as wearable EEG. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Sparse representation prevents over-fitting in the classifier by eliminating redundancies and evaluating high-frequency patterns between feature vectors. Performance of proposed methods surpass the classic bag of words algorithm for plant identification tasks.…”
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The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Published 2021“…In the present investigation, an ensemble learning-based classification algorithm, namely random subspace k-nearest neighbour (k-NN) has been proposed to classify the motor imagery (MI) data. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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