Search Results - (( developing learner selection algorithm ) OR ( java realization based algorithm ))
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1
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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2
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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3
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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4
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
5
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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6
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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7
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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8
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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9
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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10
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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Thesis -
11
An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…FAM is selected as a meta-learner to effectively train and combine the outputs of the base learners and achieve robust and accurate classification. …”
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12
Dynamic force-directed graph with weighted nodes for scholar network visualization
Published 2022“…A scholar network visualization approach is proposed to help users to explore a large number of academic publications concerning the strength of the relationship between each publication. The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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13
A Conceptual Framework to Aid Attribute Selection in Machine Learning Student Performance Prediction Models
Published 2023“…Machine learning algorithm's performance demotes with using the entire attributes and thus a vigilant selection of predicting attributes boosts the performance of the produced model. …”
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14
Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…The methodology is proposed as stacking ensemble ML and the best ML algorithms are used as a base learner to compute relative feature weights. …”
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Thesis -
15
Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration
Published 2022“…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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Final Year Project / Dissertation / Thesis
