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Found 5 papers, 3 papers with code
Unbiased Gradient Boosting Decision Tree with Unbiased Feature Importance
To this end, we provide a fine-grained analysis of bias in GBDT and demonstrate that the bias originates from 1) the systematic bias in the gain estimation of each split and 2) the bias in the split finding algorithm resulting from the use of the same data to evaluate the split improvement and determine the best split.
Generative Table Pre-training Empowers Models for Tabular Prediction
Recently, the topic of table pre-training has attracted considerable research interest.
OpenFE: Automated Feature Generation with Expert-level Performance
In the two competitions, features generated by OpenFE with a simple baseline model can beat 99. 3% and 99. 6% data science teams respectively.
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
It uses less than 5% FLOPS compared with previous SOTA methods on the largest benchmark dataset.
AutoAlpha: an Efficient Hierarchical Evolutionary Algorithm for Mining Alpha Factors in Quantitative Investment
The multi-factor model is a widely used model in quantitative investment.
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