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(Created page with "Some notes on ranking techniques ==Basics== [https://medium.com/@mayurbhangale/pointwise-pairwise-and-listwise-learning-to-rank-baf0ad76203e Pointwise, Pairwise and Listwise Learning to Rank] ===Point-wise ranking=== In point-wise ranking, you have some scores for you document <math>y_i</math> so you can train your model <math>f</math> to predict such scores in a ==Metrics== ===Cumulative Gain=== Suppose you have a list of results <math>x_1,..., x_n</math> with rel...") |
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<math> | <math> | ||
\begin{equation} | \begin{equation} | ||
NCDG_p = \frac{DCG_g(\mathbf{r})}{\max_{\mathbf{r}DCG_p(\mathbf{r}) | NCDG_p = \frac{DCG_g(\mathbf{r})}{\max_{\mathbf{r}}DCG_p(\mathbf{r})} | ||
\end{equation} | \end{equation} | ||
</math> | </math> |