Search Results - (( risk optimization method algorithm ) OR ( data evaluation method algorithm ))
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1
Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. …”
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2
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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3
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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4
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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5
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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6
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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7
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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8
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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9
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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10
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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11
Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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12
Modeling forest fires risk using spatial decision tree
Published 2011“…In addition, criteria evaluation and weighting method are most applied to evaluate the small problem containing few criteria. …”
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13
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
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14
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
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15
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
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16
Route optimization security in mobile IPv6 wireless networks: a test-bed experience
Published 2008“…An enhanced security algorithm is developed on top of MIPv6 RO to secure data. …”
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17
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
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18
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
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19
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
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20
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. …”
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