Search Results - (( java implementation mining algorithm ) OR ( pattern grading _ algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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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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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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9
Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…The optimized models classified building damage grades with an AUROC of 0.9952. Comparing machine learning algorithms yields insights. …”
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Tracking student performance in introductory programming by means of machine learning
Published 2023Conference Paper -
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)
Published 2023“…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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Pattern classifier of chemical compounds in different qualities of agarwood oil parameter using scale conjugate gradient algorithm in MLP
Published 2017“…The result showed that MLP as pattern classifier is successful classify agarwood oil quality using SCG algorithm with 100% accuracy. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)
Published 2023“…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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14
MELODY TRAINING WITH SEGMENT-BASED TILT CONTOUR FOR QURANIC TARANNUM
Published 2021“…The proposed application also provides feedback in the form of a grade and a percentage of accuracy, as determined by a melody curve similarity algorithm. …”
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Distance measure and its application to decision making, medical diagnosis, and pattern recognition problems under complex picture fuzzy sets
Published 2025“…Finally, we developed an algorithm using complex picture fuzzy environments and applied it to a practical application concerning decision making, medical diagnosis, and pattern recognition problems. ? …”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…First, this study combines SPM with Sentence Scoring method as feature-based approach and Bellman-Ford algorithm as graph-based to validate the performance of SPM. …”
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Pattern extraction for programming performance evaluation using directed apriori
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Spatial-temporal analysis using two-stage clustering and GIS-based MCDM to identify potential market regions
Published 2021“…First, time-series clustering is conducted to groups regencies/cities based on the enrolled students' patterns over time in the university. Subsequently, the origin schools' regencies/cities were clustered using the k- prototypes algorithm based on their time-series pattern category, the consistency in sending students, average cumulative grade point average (CGPA), and dropout (DO) rate. …”
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