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author | nunzip <np.scarh@gmail.com> | 2018-11-20 12:07:28 +0000 |
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committer | nunzip <np.scarh@gmail.com> | 2018-11-20 12:07:28 +0000 |
commit | 9bf16d672912104488c22efb216d309c008c3933 (patch) | |
tree | a1a1cae8047c4fa35d2d8f63297ba944ecdaac83 /report | |
parent | fcc4990e364ab0df19cec513cda90f3f49e2efae (diff) | |
download | vz215_np1915-9bf16d672912104488c22efb216d309c008c3933.tar.gz vz215_np1915-9bf16d672912104488c22efb216d309c008c3933.tar.bz2 vz215_np1915-9bf16d672912104488c22efb216d309c008c3933.zip |
Add info about dataset
Diffstat (limited to 'report')
-rwxr-xr-x | report/metadata.yaml | 4 |
1 files changed, 3 insertions, 1 deletions
diff --git a/report/metadata.yaml b/report/metadata.yaml index 99de501..c7ede78 100755 --- a/report/metadata.yaml +++ b/report/metadata.yaml @@ -17,8 +17,10 @@ abstract: | On the other hand LDA, Linear Discriminant Analysis, allows to perform a very reliable classification, generating a discriminative subspace, in which the separation between classes is easier to recognize. - In the final part we will analyze the benefits of using a combined version of the two methods using FIsherfaces. + In the final part we will analyze the benefits of using a combined version of the two methods using Fisherfaces. As we will see, the PCA-LDA ensemble will obtain much more accurate results with a very high speed of computation. + The data used includes 52 classes with 10 samples each. The number of features is 2576(since the size of the pictures is 46x56). + ... |