ML Anthology

Data Analysis Using G/SPLINES

David Rogers
NeurIPS 1991 pp. 1088-1095
/neurips/1991/rogers1991neurips-data/

Abstract

G/SPLINES is an algorithm for building functional models of data. It uses genetic search to discover combinations of basis functions which are then used to build a least-squares regression model. Because it produces a population of models which evolve over time rather than a single model, it allows analysis not possible with other regression-based approaches.

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Cite

Text

Rogers. "Data Analysis Using G/SPLINES." Neural Information Processing Systems, 1991.

Markdown

[Rogers. "Data Analysis Using G/SPLINES." Neural Information Processing Systems, 1991.](https://mlanthology.org/neurips/1991/rogers1991neurips-data/)

BibTeX

@inproceedings{rogers1991neurips-data,
  title     = {{Data Analysis Using G/SPLINES}},
  author    = {Rogers, David},
  booktitle = {Neural Information Processing Systems},
  year      = {1991},
  pages     = {1088-1095},
  url       = {https://mlanthology.org/neurips/1991/rogers1991neurips-data/}
}