Jose Talavera

We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
Cross validation is fundamental to machine learning as it provides a reliable way in which to evaluate algorithms and the overall quality of the corpora in use. In typical cross validation, the corpus is initially divided into <i>learning</i> and <i>training</i> segments, then crossed-over in successive rounds, so that each data segment is validated against(More)
  • 1