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author | Vasil Zlatanov <v@skozl.com> | 2018-12-10 17:13:06 +0000 |
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committer | Vasil Zlatanov <v@skozl.com> | 2018-12-10 17:13:06 +0000 |
commit | bbb2f0825f62842784c332ef316ffca947b368be (patch) | |
tree | 646e7b0fe18c58f65e1d4ac9e0b449655d3eb1d0 /report2 | |
parent | f6bcf2eaa1b5cb6ddfa5c91581907113d0c65d49 (diff) | |
download | vz215_np1915-bbb2f0825f62842784c332ef316ffca947b368be.tar.gz vz215_np1915-bbb2f0825f62842784c332ef316ffca947b368be.tar.bz2 vz215_np1915-bbb2f0825f62842784c332ef316ffca947b368be.zip |
Add baseline intro
Diffstat (limited to 'report2')
-rwxr-xr-x | report2/paper.md | 8 |
1 files changed, 2 insertions, 6 deletions
diff --git a/report2/paper.md b/report2/paper.md index dc07241..2173cf1 100755 --- a/report2/paper.md +++ b/report2/paper.md @@ -29,6 +29,8 @@ Alternative distance metrics exist such as jaccardian and mahalanobis, which can # Baseline Evaluation +To evaluate improvements brought by alternative distance learning metrics a baseline is established as trough nearest neighbour identification as previously described. + \begin{figure} \begin{center} \includegraphics[width=20em]{fig/baseline.pdf} @@ -55,12 +57,6 @@ Alternative distance metrics exist such as jaccardian and mahalanobis, which can \end{center} \end{figure} - -TODO: -~~ -s/kNN/NN/ -~~ - \begin{figure} \begin{center} \includegraphics[width=20em]{fig/comparison.pdf} |