From 31f4baf2297ecff899fcc11bd13439ae162ef08b Mon Sep 17 00:00:00 2001 From: Vasil Zlatanov Date: Fri, 15 Feb 2019 17:42:36 +0000 Subject: Quantise s/s/z --- report/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/report/paper.md b/report/paper.md index 89ad94e..58ec125 100644 --- a/report/paper.md +++ b/report/paper.md @@ -148,7 +148,7 @@ In many applications the increase in training time would not justify the small i For the `Caltech_101` dataset, a RF codebook seems to be the most suitable method to perform RF classification. -The `water_lilly` is the most misclassified class, both for K-means and RF codebook (refer to figures \ref{fig:km_cm} and \ref{fig:p3_cm}). This indicates that the quantised descriptors obtained from the class do not provide for very discriminative splits, resulting in the prioritsation of other features in the first nodes of the decision trees. +The `water_lilly` is the most misclassified class, both for K-means and RF codebook (refer to figures \ref{fig:km_cm} and \ref{fig:p3_cm}). This indicates that the quantized descriptors obtained from the class do not provide for very discriminative splits, resulting in the prioritsation of other features in the first nodes of the decision trees. # References -- cgit v1.2.3