srowen commented on a change in pull request #23589: [SPARK-26351][mllib]Update
doc and minor correction in the mllib evaluation metrics
URL: https://github.com/apache/spark/pull/23589#discussion_r249248310
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File path: docs/mllib-evaluation-metrics.md
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@@ -439,21 +439,21 @@ $$rel_D(r) = \begin{cases}1 & \text{if $r \in D$}, \\ 0
& \text{otherwise}.\end{
Precision at k
</td>
<td>
- $p(k)=\frac{1}{M} \sum_{i=0}^{M-1} {\frac{1}{k}
\sum_{j=0}^{\text{min}(\left|D\right|, k) - 1} rel_{D_i}(R_i(j))}$
+ $p(k)=\frac{1}{M} \sum_{i=0}^{M-1} {\frac{1}{k}
\sum_{j=0}^{\text{min}(\left|R_i\right|, k) - 1} rel_{D_i}(R_i(j))}$
</td>
<td>
- <a
href="https://en.wikipedia.org/wiki/Information_retrieval#Precision_at_K";>Precision
at k</a> is a measure of
+ <a
href="https://en.wikipedia.org/wiki/Evaluation_measures_(information_retrieval)#Precision_at_K">Precision
at k</a> is a measure of
how many of the first k recommended documents are in the set of true
relevant documents averaged across all
users. In this metric, the order of the recommendations is not taken
into account.
</td>
</tr>
<tr>
<td>Mean Average Precision</td>
<td>
- $MAP=\frac{1}{M} \sum_{i=0}^{M-1} {\frac{1}{\left|D_i\right|}
\sum_{j=0}^{Q-1} \frac{rel_{D_i}(R_i(j))}{j + 1}}$
+ $MAP=\frac{1}{M} \sum_{i=0}^{M-1} {\frac{1}{\left|R_i\right|}
\sum_{j=0}^{\left|R_i\right|-1} \frac{rel_{D_i}(R_i(j))}{j + 1}}$
Review comment:
I'm not sure if dividing by R_i is right here, but see below.
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