Search Results - (((( pattern learning algorithm ) OR ( self learning algorithm ))) OR ( pattern bat algorithm ))*
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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Naive bayes-guided bat algorithm for feature selection.
Published 2013“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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Bat algorithm for rough set attribute reduction
Published 2023“…In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”
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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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Multilevel learning in Kohonen SOM network for classification problems
Published 2006“…Classification is one of the most active research and application areas of neural networks. Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK
Published 2011“…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Self-Organizing Feature (SOM) was used to visualize and identify the relationship and pattern between factors affecting mortality after ACS. …”
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Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making
Published 2024“…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood
Published 2015“…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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Preserving the topology of self-organizing maps for data analysis: A review
Published 2020“…In Kohonen's Self-Organizing Maps (SOM) algorithm, preserving the map structure to represent the real input patterns appears to be a significant process. …”
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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
Published 2023“…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection
Published 2021“…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN
Published 2011“…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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