Empirical_Study_of_Ensemble_Learning_Methods
vswift
Empirical_Study_of_Ensemble_Learning_Methods | vswift | |
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1 | 1 | |
10 | 1 | |
- | - | |
0.0 | 8.9 | |
over 3 years ago | 30 days ago | |
R | R | |
- | MIT License |
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Empirical_Study_of_Ensemble_Learning_Methods
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[P] Which Machine Learning Classifiers are best for small datasets? An empirical study
I've actually made the same kind of graph before. In this image: each point is the average of 5 out-of-fold predictions for one trial of k-fold cross-validation. I repeated the procedure 40 times to visualize the out-of-fold accuracy on the Wisconsin diagnostic breast cancer data set (560 observations on 30 numeric variables). I evaluated 14 models for classification:
vswift
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Seeking Feedback on my R Package for Categorical Model Validation
Here is the repo if anyone is interested: https://github.com/donishadsmith/vswift
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