Search Results - (( java application mining algorithm ) OR ( var estimation using algorithm ))
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Direct approach for mining association rules from structured XML data
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Thesis -
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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. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Article -
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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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Conference or Workshop Item -
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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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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
7
Validation of combine white noise using simulated data
Published 2016“…The same generated EGARCH data are transformed to obtain CWN data and VAR data for the estimation of CWN and VAR.Each CWN results outperformed every result of the existing models.These results confirm that CWN is the appropriate model for estimation.The CWN model fit best in the transformed 200 sample sizes of EGARCH generated data with moderate leverage and moderate skewness. …”
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Article -
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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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Thesis -
9
Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models
Published 2004“…Methods for correcting the outliers and splitting the heterogeneous data are proposed. The EM algorithm is applied to split the heterogeneous data, and the estimated parameters are used to correct the outlying data using the Mahalanobis Distance. …”
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Thesis -
10
Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning
Published 2025“…Adaptive Moment Estimation (Adam) and Adaptive Nesterov Accelerated Gradi- ent (Adan), two well-known optimizers, are widely used in deep learning for their ability to handle large-scale data and complex models efficiently. …”
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Proceeding Paper
