Search Results - (( data classification method algorithm ) OR ( evolution extraction method algorithm ))
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1
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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5
Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Simultaneously, news sentiment analysis techniques were used to discover the polarity of news according to each factor. From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
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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. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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11
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The experimental results on artificial data sets and real-world data sets (from UCI Repository) show that the new method could improve both the efficiency and accuracy of pattern classification. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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14
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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15
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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16
Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. …”
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An efficient and effective case classification method based on slicing
Published 2006“…The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Thus, both proposed imbalanced LR-based methods is simple and effective for classification of imbalanced data sets and have promising results.…”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution
Published 2012“…The two diode model of a solar cell is used as the basis for the extraction problem. The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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