Tree-based machine learning methods for survey research

@article{Kern2019TreebasedML,
  title={Tree-based machine learning methods for survey research},
  author={C. Kern and T. Klausch and F. Kreuter},
  journal={Survey research methods},
  year={2019},
  volume={13},
  pages={73-93}
}
  • C. Kern, T. Klausch, F. Kreuter
  • Published 2019
  • Computer Science
  • Survey research methods
  • Predictive modeling methods from the field of machine learning have become a popular tool across various disciplines for exploring and analyzing diverse data. These methods often do not require specific prior knowledge about the functional form of the relationship under study and are able to adapt to complex non-linear and non-additive interrelations between the outcome and its predictors while focusing specifically on prediction performance. This modeling perspective is beginning to be adopted… CONTINUE READING
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    References

    SHOWING 1-10 OF 83 REFERENCES
    An Introduction to Machine Learning Methods for Survey Researchers
    • 17
    • PDF
    Surveying the Forests and Sampling the Trees: An overview of Classification and Regression Trees and Random Forests with applications in Survey Research
    • 6
    • Highly Influential
    • PDF
    Extremely randomized trees
    • 2,810
    • PDF
    The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition
    • 13,457
    • PDF
    Classification and Regression by randomForest
    • 10,519
    • PDF
    An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets
    • 63
    • PDF
    Bagging predictors
    • 12,367
    • PDF