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1
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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2
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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3
Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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4
Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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5
Advanced flood prediction at forest with rainfall data using various machine learning algorithms
Published 2024“…The aim is to classify and predict floods in advance with rain data patterns of India using spatio-temporal logic. Two Classification algorithms are used to achieve the maximum accuracy namely K-Nearest Neighbour with a sample size=5 and Logistic Regression with a sample size=5 for continues iterations. …”
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6
A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification
Published 2015“…The idea of developing FAM-OELM is motivated by the ELM concept proposed by Huang et al., for being an efficient learning algorithm that provides better generalization performance at a much faster learning speed. …”
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7
Financial time series predicting using machine learning algorithms
Published 2013“…Subsequently, Dynamic Time Warping (DTW) algorithm is utilised through brute force to predict the trend movement. …”
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8
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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9
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…Negative Selection algorithm (NSA), Clonal Selection algorithm (CSA) and Immune Network algorithm (INA); and model analysis. …”
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10
Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Book Section -
11
Web usage mining for UUM learning care using association rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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12
Alternate methods for anomaly detection in high-energy physics via semi-supervised learning
Published 2020“…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
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13
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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14
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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15
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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16
Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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17
Comparative study of machine learning algorithms in data classification
Published 2025“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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18
The effect of adaptive parameters on the performance of back propagation
Published 2012“…The results show that the proposed algorithm extensively improves the learning process of conventional Back Propagation algorithm.…”
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19
Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893)
Published 2017“…The spike encoding was used for feature extraction. The algorithm for this learning model adopted the reward-modulated STDP. …”
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Monograph -
20
Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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