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1
The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment
Published 2007“…Region growing segmentation and radial basis function algorithms are considered a powerful tool to minimize the mixed pixel classification error.…”
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2
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Thesis -
3
Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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4
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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5
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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6
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Various data mining techniques are being used by researchers of different domains to analyze data and extract valuable information from a data set for further use. …”
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7
Data Classification and Its Application in Credit Card Approval
Published 2004“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Final Year Project -
8
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Based on the experiment results, the classification method using the TIP approach has successfully performed rules generation and classification tasks as required during a classification operation. …”
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9
Tree-based contrast subspace mining method
Published 2020“…Those subspaces are termed as contrast subspaces. All existing mining contrast subspace methods (i.e. CSMiner and CSMiner-BPR) use density-based likelihood contrast scoring function to estimate the likelihood of a query object to target class against other class in a subspace. …”
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10
Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm
Published 2021“…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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11
An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…The first objective of this study is to improve a new algorithm technique for classification. The new algorithm come from a combination of an ideas of k-NN algorithm and ensemble concept. …”
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12
Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023“…IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. …”
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13
Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance
Published 2003“…Neural network approaches, while reasonably accurate at classification, give no information ahout the relationship between the unseen case and the classified items that is useful to biologist. In contrast, in this paper we use a generalized radial basis function (GRBF) neural network architecture 'that generates fuzzy classification rules that could he used for further knowledge discovery. …”
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Proceeding -
14
Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…The future recommendation for this project is to build a classification model for Malay reviews and explore other algorithms which could gain better accuracy by capturing more contextual meanings in the reviews such as BERT.…”
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15
Discovering decision algorithm from a distance relay event report
Published 2009“…This derived algorithm, aptly known as relay CD-prediction rules, can later be used as a knowledge base in support of a protection system analysis expert system to predict, validate or even diagnose future unknown relay events. …”
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16
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…The developed logic mining will be used to analyze the Alzheimer's Disease Neuroimaging Initiative dataset.…”
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17
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Also a new algorithm for finding the initial point is proposed. …”
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18
Data mining of protein sequences with amino acid position-based feature encoding technique
Published 2014“…The classification results indicate that the proposed encoding technique with a decision tree classification algorithm has achieved 85.9 classification accuracy over the Yeast protein sequence dataset. …”
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19
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Meanwhile, the DT classification using the LS approach produced the highest overall accuracy of 87% and a kappa coefficient of 0.80. …”
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20
RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018“…The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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