Dec 9, 2018 · This article is aimed at the low accuracy of student weariness prediction in education and the poor prediction effect of traditional ...
Dec 10, 2018 · This article is aimed at the low accuracy of student weariness prediction in education and the poor prediction effect of traditional ...
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Struggling with understanding RandomForest model with SMOTE
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May 25, 2023 · My code is telling me that my base model is performing at 96% on it's training data, 55% on it's test data. And my SMOTE model is performing at ~96% on both.
Missing: Weariness | Show results with:Weariness
Jul 15, 2024 · An RF classifier combined with SMOTE also provided good results in predicting depression using the Korea Welfare Panel Study (KoWePS).
Missing: Weariness | Show results with:Weariness
Sep 4, 2023 · The results demonstrated that the Random Forest classifier with SMOTE-Tomek achieved a remarkable accuracy score of 99.69%. Gowri and Saranya [ ...
Missing: Weariness | Show results with:Weariness
Feb 15, 2023 · Whether or not to use SMOTE when you have an imbalanced class in a random forest classification model depends on your desired outcome.
Missing: Weariness | Show results with:Weariness
This study aimed at developing a fatigue level prediction model for Back-Support Industrial Exoskeletons (BSIEs) using wearable sensors.
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This paper aims to investigate the stability of SMOTE-based oversampling techniques. Moreover, a series of stable SMOTE-based oversampling techniques are ...
The XGBoost classifier performs much better than the random forest classifier when it comes to predicting the minority class. However, it still fails to ...