Search Results - (( developing learner selection algorithm ) OR ( java optimization strategy algorithm ))

Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite by Suali, Anjila J., Nuraminah Ramli, Rozmie Razif Othman, Hasneeza Liza Zakaria, Iszaidy Ismail, Nor Shahida Mohd Jamail, Rimuljo Hendradi, Nurol Husna Che Rose

“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). The study compares the performance of WOA with various existing strategies, such as Greedy, Density, TVG, Union, ParaOrder, ReqOrder, ITTDG, AURA, Java Algorithm (CTJ), TTSGA, and AFA. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

“…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Agustina Pertiwi, Dwika Ananda, Subhan, Subhan, Jumanto, Jumanto, Dasril, Yosza, swanto, Iswanto

“…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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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Agustina Pertiwi b, Dwika Ananda, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

“…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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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

“…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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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Much Aziz Muslim, Much Aziz Muslim, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

“…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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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi b, Dwika Ananda Agustina Pertiwi b, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

“…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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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Nikmah, Tiara Lailatul, Dwika Ananda Agustina Pertiwi b, Dwika Ananda Agustina Pertiwi b, Subhan b, Subhan b, Jumanto, Jumanto, Nikmah, Tiara Lailatul, Agustina Pertiwi, Dwika Ananda, Iswanto, Iswanto

“…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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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning* by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

“…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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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning by Muslim, Much Aziz, Tiara Lailatul Nikmah, Tiara Lailatul Nikmah, Dwika Ananda Agustina Pertiwi, Dwika Ananda Agustina Pertiwi, Subhan, Subhan, Jumanto, Jumanto, Yosza Dasril, Yosza Dasril, Iswanto, Iswanto

“…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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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection by Shing, Chiang Tan, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Lim, Pey, Yun Goh, Chee, Peng Lim

“…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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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

“…Firstly, a Priority-Based Fair Scheduling (PBFS) algorithm has been introduced to schedule jobs so that jobs can access the required resources at optimal times. …”
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A Conceptual Framework to Aid Attribute Selection in Machine Learning Student Performance Prediction Models by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…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. …”

Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…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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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

“…There is also a need to consider implementing this strategy for dynamic object-oriented languages such as Python, Lisp, and Smalltalk.…”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

“…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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