Comprehensible Interpretation of Relief's Estimates

@inproceedings{RobnikSikonja2001ComprehensibleIO,
  title={Comprehensible Interpretation of Relief's Estimates},
  author={Marko Robnik-Sikonja and Igor Kononenko},
  booktitle={ICML},
  year={2001}
}
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

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