Search Results - (( variable training needs algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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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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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 -
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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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Enhancing the entrepreneurial intention of the retiring military personnel through entrepreneurial training
Published 2017“…It was also found that the entrepreneurial training moderated the relationship between two of the independent variables (entrepreneurial finance and physical facilities) and entrepreneurial intention. …”
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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Design of artificial intelligence based speed estimator for DC drives / Pauziah Saleh
Published 2006“…The training took only few minutes on a PC for the 30000 input-output training data . …”
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)
Published 2024“…Recursive Feature Elimination (RFE) was employed for feature selection, and we trained seven supervised classifiers. Grid Search was used to optimize the hyperparameters of each algorithm. …”
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Design of Artificial Neural Network (ANN) based rotor speed estimator for DC drives / Siti Mutrikah Abd Mokhsin
Published 2002“…For this purpose the Levenberg-Marquardt back-propagation algorithm was used. The training took only a few minutes on a PC and for this purpose 30000 inputoutput training data were used. …”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration
Published 2022“…Nonetheless, based on the literature review performed, machine learning models are data-hungry in nature, which increases the difficulty of training a model from scratch. The data hunger of machine learning models can be classified into two categories, namely the qualitative hunger (where machine learning models need for various features for training) and quantitative hunger (need for a vast amount of historical data for training). …”
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Final Year Project / Dissertation / Thesis -
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Dynamics and control of underactuated systems with applications in robotics / Ahmad Azlan Mat Isa … [et al.]
Published 2011“…The robot can directly determine the position of its passive joint, and can, therefore, completely eliminate the need for any system modeling. Even though it is very difficult in practice, data used in this study were recorded experimentally from sensors fixed on robot's joints to overcome the effect of kinematics uncertainties presence in the real world such as ill-defined linkage parameters and backlashes in gear trains. …”
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Research Reports -
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Evaluation of postgraduate academic performance using artificial intelligence models
Published 2022“…The Gaussian process regression (GPR) model with squared exponential kernel algorithm achieved 71 of the CGPA variation. The model achieved 0.095 CGPA points for both training and evaluation errors. …”
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Evaluation of postgraduate academic performance using artificial intelligence models
Published 2022“…The Gaussian process regression (GPR) model with squared exponential kernel algorithm achieved 71 of the CGPA variation. The model achieved 0.095 CGPA points for both training and evaluation errors. …”
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Evaluation of postgraduate academic performance using artificial intelligence models
Published 2022“…The Gaussian process regression (GPR) model with squared exponential kernel algorithm achieved 71 of the CGPA variation. The model achieved 0.095 CGPA points for both training and evaluation errors. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…In addition, the manual segmentation is subjective depending on the expert's experience. Hence, the need to develop automatic segmentation algorithms has rapidly increased along with the increased need of diagnostic tools for assisting medical practitioners, especially in the absence of radiologists. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…In addition, the manual segmentation is subjective depending on the expert's experience. Hence, the need to develop automatic segmentation algorithms has rapidly increased along with the increased need of diagnostic tools for assisting medical practitioners, especially in the absence of radiologists. …”
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