High Dimensional Human Guided Machine Learning
September 04, 2016 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Eric Holloway, Robert Marks
arXiv ID
1609.00904
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LG,
stat.ML
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Have you ever looked at a machine learning classification model and thought, I could have made that? Well, that is what we test in this project, comparing XGBoost trained on human engineered features to training directly on data. The human engineered features do not outperform XGBoost trained di- rectly on the data, but they are comparable. This project con- tributes a novel method for utilizing human created classifi- cation models on high dimensional datasets.
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