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Update README.md

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@@ -24,6 +24,7 @@ Sources:
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  Dataset Information:
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  The original data directory contains the binary images (masks) of the leaf samples (colour images not included). There are three features for each image: Shape, Margin and Texture. For each feature, a 64 element vector is given per leaf sample. These vectors are taken as a contiguous descriptor (for shape) or histograms (for texture and margin). So, there are three different files, one for each feature problem:
 
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  ‘data_Sha_64.txt’ -> prediction based on shape
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  ‘data_Tex_64.txt’ -> prediction based on texture
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  ‘data_Mar_64.txt’ -> prediction based on margin
 
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  Dataset Information:
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  The original data directory contains the binary images (masks) of the leaf samples (colour images not included). There are three features for each image: Shape, Margin and Texture. For each feature, a 64 element vector is given per leaf sample. These vectors are taken as a contiguous descriptor (for shape) or histograms (for texture and margin). So, there are three different files, one for each feature problem:
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+
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  ‘data_Sha_64.txt’ -> prediction based on shape
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  ‘data_Tex_64.txt’ -> prediction based on texture
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  ‘data_Mar_64.txt’ -> prediction based on margin