Search Results - (( data classification using algorithm ) OR ( automatic classification using algorithm ))
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the FID3 algorithm. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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Text Extraction Algorithm for Web Text Classification
Published 2010“…In this study, the experiment was conducted on five English educational websites. The created data sets are then classified using Naive-Bayes and C4.5 algorithms provided in WEKA application. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…The fuzzy-ID3 algorithm with association function implementation (FID3-AF) is proposed as a classification technique for breast cancer detection. …”
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Evaluation of fall detection classification approaches
Published 2012“…The acceleration data with a total data of 6962 instances and 29 attributes were used to evaluate the performance of the different classification algorithm. …”
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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal
Published 2017“…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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Automatic Classification of Cervix Type
Published 2019“…Due to that, in this study, few algorithms were developed by using image classification methods to correctly classify the cervix types based on cervical images by using segmentation and classification method. …”
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Waste classification using support vector machine with SIFT-PCA feature extraction
Published 2020“…This research proposes waste image classification to support automatic waste sorting using Support Vector Machine (SVM) classification algorithm and SIFT-PCA (Scale Invariant Feature Transform - Principal Component Analysis) feature extraction. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Classification of JPEG files by using extreme learning machine
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Among all these techniques, classification is one of the most commonly used tasks in data mining, which is used by many researchers to classify instances into two or more pre-determined classes. …”
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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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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…In order to develop this model classification and prototype, 480 Twitter’s messages were used as training data and 120 Twitter’s messages for testing data to determine the accuracy of the classification model. …”
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A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher's Iris data set and shown to be very competitive.…”
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A literature review on text classification and sentiment analysis approaches
Published 2021“…In the system architecture, same as text classification, the complete classification systemmainly contains data acquisition, data pre-process, feature extraction, classification algorithm and result output.TheWeb crawler usually be used in first step, the URL Link, hashtags, Non-Chinese text should be removed in second step. …”
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Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment
Published 2013“…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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