Comprehensible Interpretation of Relief's Estimates

  title={Comprehensible Interpretation of Relief's Estimates},
  author={Marko Robnik-Sikonja and Igor Kononenko},
Attribute estimation is an important machine learning problem. It is contained in many tasks, e.g., feature subset selection, constructive induction, decision and regression tree building. Relief algorithms are one of the most successful heuristic measures for solving this problem. The quality estimates of the Relief algorithms have commonly been interpreted as the difference of two probabilities, which make them rather difficult for human comprehension. We present a new insight on how these… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.
11 Citations
14 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 11 extracted citations


Publications referenced by this paper.
Showing 1-10 of 14 references

Use of contextual information for feature ranking and discretization

  • S. J. Hong
  • IEEE transactions on knowledge and data…
  • 1997
Highly Influential
1 Excerpt

Modeling the effects of environmental conditions on apparent photosynthesis of Stipa bromoides by machine learning tools

  • M. Šikonja, S. Sgardelis
  • 2000

Similar Papers

Loading similar papers…