Abstract
for machine learning in general,
and music genre recognition in particular.
We show analytically that the probability of error for IGS
is higher than naive Bayes classification with zero-one loss (NB).
We show empirically that IGS does not perform well,
even for data that satisfies all its assumptions.
| Original language | English |
|---|---|
| Journal | I E E E Signal Processing Letters |
| Volume | 20 |
| Issue number | 11 |
| Pages (from-to) | 1050-1053 |
| Number of pages | 4 |
| ISSN | 1070-9908 |
| DOIs | |
| Publication status | Published - Nov 2013 |
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Revisiting Inter-Genre Similarity. / Sturm, Bob L.; Gouyon, Fabien.
In: I E E E Signal Processing Letters, Vol. 20, No. 11, 11.2013, p. 1050-1053.Research output: Contribution to journal › Journal article › Research › peer-review
TY - JOUR
T1 - Revisiting Inter-Genre Similarity
AU - Sturm, Bob L.
AU - Gouyon, Fabien
PY - 2013/11
Y1 - 2013/11
N2 - We revisit the idea of ``inter-genre similarity'' (IGS)for machine learning in general,and music genre recognition in particular.We show analytically that the probability of error for IGSis higher than naive Bayes classification with zero-one loss (NB).We show empirically that IGS does not perform well,even for data that satisfies all its assumptions.
AB - We revisit the idea of ``inter-genre similarity'' (IGS)for machine learning in general,and music genre recognition in particular.We show analytically that the probability of error for IGSis higher than naive Bayes classification with zero-one loss (NB).We show empirically that IGS does not perform well,even for data that satisfies all its assumptions.
U2 - 10.1109/LSP.2013.2280031
DO - 10.1109/LSP.2013.2280031
M3 - Journal article
VL - 20
SP - 1050
EP - 1053
JO - I E E E Signal Processing Letters
JF - I E E E Signal Processing Letters
SN - 1070-9908
IS - 11
ER -