Search Results - (( based classifications based algorithm ) OR ( learning classification parallel algorithm ))
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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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2
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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3
Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets
Published 2025“…The k-Nearest Neighbour (k-NN) algorithm is one of the most widely used Instance-Based Learning methods due to its simplicity and ease of implementation. …”
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5
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The incorporation of a single parallel hidden layer feed-forward neural network to the Fast Learning Network (FLN) architecture gave rise to the improved Extreme Learning Machine (ELM). …”
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6
Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN)
Published 2011“…ANNs are particularly useful for complex pattern recognition and classification tasks. The capability of learning from examples, the ability to reproduce arbitrary non-linear functions of input, and the highly parallel and regular structure of ANNs make them especially suitable for pattern recognition tasks. …”
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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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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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10
Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification
Published 2024“…Recently, the swarm-based hybrid algorithms have given significant performance in cancer classification. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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12
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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13
Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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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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Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
Published 2014“…Based on certain priority rules, SSPC makes classification decisions for each flow. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition
Published 2016“…This research is mainly focused on creating a new algorithm based on classification technique to calculate food calorie intake in real-time. …”
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An efficient and effective case classification method based on slicing
Published 2006“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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