Search Results - (( developing features data algorithm ) OR ( java application mining algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Direct approach for mining association rules from structured XML data
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…This is due to the features selected in this classifier is over-fitted to the training data and not generalized for variations in testing data. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…However, these semi-supervised multi-task selection feature algorithms are unable to naturally handle the multi-view data since they are designed to deal with single-view data. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…Thus, to solve these problems, feature selection can be used to select optimal subset of features and reduce the data dimensionality. …”
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks
Published 2019“…However, these semisupervised multitask selection feature algorithms are unable to naturally handle the multiview data since they are designed to deal single-view data. …”
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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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Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali
Published 2022“…Hence, the development of DIS algorithm has successfully help in producing the edges features on a particular surface topography that are accurate and in line with what has been agreed based on human perception.…”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Development Of Fall Risk Clustering Algorithm In Older People
Published 2020“…The proposed algorithm consists of several stages, includes data pre-processing, feature selection, feature extraction, clustering and characteristic interpretation. …”
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Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
Published 2016“…For this research, the meaningful information that will be extracting is eye feature. Methodology of this research consists of Planning and Analysis, Data Collection, Algorithm Design and Development and Testing. …”
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Facial features point localization using modified SIFT scale space / Zulfikri Paidi
Published 2020“…Surface change creates high-dimensional data during feature extraction work. There are many algorithms proposed for recognition of facial expressions, including SIFT algorithms that are considered superior in performing feature extraction. …”
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Optimized feature construction methods for data summarizations of relational data
Published 2014“…The summarized data will then be fed to any classification algorithm to perform the classification task. …”
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. …”
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SVM for network anomaly detection using ACO feature subset
Published 2016“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. …”
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