Search Results - (( java application sensor algorithm ) OR ( variables classification approach algorithm ))
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Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…A new direction for ACO is to optimize continuous and mixed (discrete and continuous) variables. Support Vector Machine (SVM) is a pattern classification approach originated from statistical approaches. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…Support Vector Machine (SVM) is a present day classification approach originated from statistical approaches.Two main problems that influence the performance of SVM are selecting feature subset and SVM model selection. …”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…Experimental results obtained from the proposed algorithm are better compared with other approaches in terms of classification accuracy and feature subset selection.…”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Eight benchmark datasets from UCI were used in the experiments to validate the performance of the proposed algorithms. Experimental results obtained from the proposed algorithms are better when compared with other approaches in terms of classification accuracy. …”
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Integrated ACOR/IACOMV-R-SVM Algorithm
Published 2017“…Support Vector Machine (SVM), which originates from the statistical approach, is a present day classification technique. …”
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Observer-based fault detection with fuzzy variable gains and its application to industrial servo system
Published 2020“…Also, a scoring algorithm has been implemented, to evaluate the classification ability of the algorithm and the early fault detection ability. …”
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Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling
Published 2018“…Secondly, the data will then be tested and trained with KNN and SVM algorithms. We conduct subject-dependent as well as subject-independent classifications in order to compare intra-against inter-subject variability, respectively in VR EEG-based emotion modeling. …”
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New Algorithm of Location Model based on Robust Estimators and Smoothing Approach
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Classification Of Cervical Cancer Stage From Pap Smear Tests
Published 2019“…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The simulation results on the benchmark medical datasets revealed that the proposed SCSO-KNN approach has outperformed comparative algorithms with an average classification accuracy of 93.96 by selecting 14.2 features within 1.91 s. …”
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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. …”
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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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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…All algorithms showed more stability and accuracy when training size applied is more than 6% by the Equal Sample Rate (ESR) method with six variables. …”
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