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Found 7 papers, 0 papers with code
Factor Importance Ranking and Selection using Total Indices
Factor importance measures the impact of each feature on output prediction accuracy.
Asset Bundling for Wind Power Forecasting
This approach effectively introduces an auxiliary learning task (predicting the bundle-level time series) to help the main learning tasks.
Optimal Ratio for Data Splitting
It is common to split a dataset into training and testing sets before fitting a statistical or machine learning model.
Data Twinning
In this work, we develop a method named Twinning, for partitioning a dataset into statistically similar twin sets.
SPlit: An Optimal Method for Data Splitting
In this article we propose an optimal method referred to as SPlit for splitting a dataset into training and testing sets.
Composite Gaussian process models for emulating expensive functions
A new type of nonstationary Gaussian process model is developed for approximating computationally expensive functions.
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