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authorVasil Zlatanov <v@skozl.com>2018-12-14 11:52:02 +0000
committerVasil Zlatanov <v@skozl.com>2018-12-14 11:52:02 +0000
commit42c214aedbfbda826c617e5081169dd8319b0c51 (patch)
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Remove spaces around lambda
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@@ -199,7 +199,7 @@ improved rank-list: $d^*(p,g_i)=(1-\lambda)d_J(p,g_i)+\lambda d(p,g_i)$.
The goal is to learn optimal values for $k_1,k_2$ and $\lambda$ using the training set,
such that an improved Top-1 identification accuracy can be found.
This is done using a multi-direction search algorithm to estimate $k_{1_{opt}}$ and $k_{2_{opt}}$
-and an exhaustive search for $\lambda$ from $ \lambda = 0 $ (exclusively Jaccard distance) to $ \lambda = 1 $ (only original distance)
+and an exhaustive search for $\lambda$ from $\lambda = 0$ (exclusively Jaccard distance) to $\lambda = 1$ (only original distance)
in steps of 0.1. The results obtained through this approach suggest: $k_{1_{opt}}=9, k_{2_{opt}}=3, 0.1\leq\lambda_{opt}\leq 0.3$.
To verify optimisation of $k_{1_{opt}}$, $k_{2_{opt}}$ heat plots were performed heat on