Search Results - (( java implementation mining algorithm ) OR ( basic classification means 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 -
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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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4
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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Final Year Project / Dissertation / Thesis -
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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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Improved normalization and standardization techniques for higher purity in K-means clustering
Published 2016“…The K-means algorithm is a famous and fast technique in non-hierarchical cluster 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
Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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10
Students Activity Recognition By Heart Rate Monitoring In Classroom Using K-means Classification
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Modelling of clinical risk groups (CRGs) classification using FAM
Published 2006“…FAM is a fast learning algorithm and used less epoch training [4]. Based on its performance in doing the classification, FAM is theoretically suitable to do the CRGs classification. …”
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12
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…First, the BrC detection model is developed to diagnose BrT basic types like benign and malignant. Second, the BrT classification model is developed to diagnose subtypes of benign and malignant tumors. …”
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13
Fuzzy C means imputation of missing values with ant colony optimization
Published 2020“…This paper proposes a improved method of imputation by employing a new version of Fuzzy c Means (FCM) which hybridized with Evolutionary Algorithm to handle missing values problem. …”
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Early detection of spots high water saturation for landslide prediction using thermal imaging analysis
“…There are three segmentation algorithm used in this study such as HSV, K-Means and Feature Matching. …”
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Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation
Published 2016“…Meanwhile, a set of descriptors corresponding to Elliptic Fourier Features shape description is extracted for each defect and is evaluated for each cluster to use for clustering and classification part. The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. …”
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17
Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing
Published 2014“…The data was collected from the Machine Learning Repository Dataset in the University of California Irvine (UCI).This experiment compares hybrid K-Means + NN with basic NN. The result shows the improvement of accuracy from 91.53% to 91.59%, recall 22.15% to 27.7% and F-Measure 44.23% but not to precision from 61.69% to 60.75%.…”
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18
Malay continuous speech recognition using continuous density hidden Markov model
Published 2007“…With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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Early detection of high water saturation spots for landslide prediction using thermal image analysis
Published 2018“…There are three segmentation algorithm used in this study which are HSV, K-Means and Feature Matching. …”
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