Learning vector quantization: Difference between revisions

Revision as of 01:09, 23 May 2025

Revision as of 01:10, 23 May 2025

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#* If <math>w_j</math> and <math>x_i</math> have the same class, and <math>w_k</math> and <math>x_i</math> have different classes, then <math>w_j \leftarrow w_j + \alpha_t(x_i - w_j)</math> and <math>w_k \leftarrow w_k - \alpha_t(x_i - w_k)</math>.

#* If <math>w_k</math> and <math>x_i</math> have the same class, and <math>w_j</math> and <math>x_i</math> have different classes, then <math>w_j \leftarrow w_j - \alpha_t(x_i - w_j)</math> and <math>w_k \leftarrow w_k + \alpha_t(x_i - w_k)</math>.

#* If <math>w_j</math> and <math>w_k</math> and <math>x_i</math> have the same class, then <math>w_j \leftarrow w_j - \epsilon\alpha_t(x_i - w_j)</math> and <math>w_k \leftarrow w_k + \epsilon\alpha_t(x_i - w_k)</math>.

#* If <math>w_k</math> and <math>x_i</math> have different classes, and <math>w_j</math> and <math>x_i</math> have different classes, then the original paper simply does not explain what happens in this case.

# Otherwise, skip.