Optimal Ridge Detection using Coverage Risk

We introduce the concept of coverage risk as an error measure for density ridge estimation. The coverage risk generalizes the mean integrated square error to set estimation. We propose two risk estimators for the coverage risk and we show that we can select tuning parameters by minimizing the estimated risk. We study the rate of convergence for coverage risk and prove consistency of the risk estimators. We apply our method to three simulated datasets and to cosmology data. In all the examples, the proposed method successfully recover the underlying density structure.

• Publication year

  2015

• Venue

  Neural Information Processing Systems

• Publication date

  2015-06-07

• Fields of study

  Mathematics, Physics, Computer Science

• Identifiers
  arXiv 1506.02278
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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