Search Results - (( java application mining algorithm ) OR ( binary classification means algorithm ))
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Direct approach for mining association rules from structured XML data
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Thesis -
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Consequently, optimization algorithms including binary gravitation search algorithm (BGSA) and binary particle swarm optimization (BPSO), were employed to identify the optimal channels for gender classification. …”
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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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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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Final Year Project / Dissertation / Thesis -
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning
Published 2021“…A total of 7 different classification algorithms were used to predict between 6 levels of CF, the Robust and Non-Robust groups, as well as the Robust and Frail with MCI groups. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Segmentation Assisted Object Distinction For Direct Volume Rendering
Published 2013“…A set of image processing techniques are creatively employed in the design of K-means based hybrid segmentation algorithm.…”
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Thesis -
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The identification of oreochromis niloticus feeding behaviour through the integration of photoelectric sensor and logistic regression classifier
Published 2018“…The signals acquired from the sensors are converted into binary data. The hunger behaviour classes are determined through k-means clustering algorithm, i.e., satiated and unsatiated. …”
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Conference or Workshop Item -
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Enhanced extreme learning machine for general regression and classification tasks
Published 2020“…The method is developed for regression task by using mean/ median of ELM training errors which is then used as threshold for separating the training data and converting the continuous targets to binary. …”
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Thesis -
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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 -
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Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing
Published 2014“…This research concerns on binary classification which is classified into two classes. …”
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Thesis -
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An Optimized Semantic Segmentation Framework for Human Skin Detection
Published 2024“…The model produced satisfactory performances even with a strict split of 50 %, confirming the high efficiency of the proposed framework. The mean Jaccard index and Dice similarity measures evaluated between the annotated and predicted mask ranged from 0.80 to 0.93 in the binary classification of pixels as “skin” versus “background”. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…However, their performance is slightly inferior to that of support vector machines for binary classification of chemical structures into drug and non drug compounds.…”
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Monograph -
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Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection
Published 2024“…Additionally, standard deviation and proposed adaptive K-means algorithms have been employed to minimize the generated rules by ANFIS from the proposed hybrid models. …”
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Thesis -
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa
Published 2018“…Inclusive with the design of UFLS is a new module referred as Load Shedding Module (LSM). Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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Thesis -
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Assessment of predictive models for chlorophyll-a concentration of a tropical lake.
Published 2011“…RMSE is based on the level of error of prediction whereas AUC is based on binary classification task. CONCLUSIONS: Overall, HEA produced the best performance in terms of RMSE, r, and AUC values. …”
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Assessment of predictive models for chlorophyll-a concentration of a tropical lake.
Published 2011“…RMSE is based on the level of error of prediction whereas AUC is based on binary classification task. CONCLUSIONS: Overall, HEA produced the best performance in terms of RMSE, r, and AUC values. …”
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