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make the library label agnostic #252
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Is this still relevant @arthurPignet ? |
Yes it is. The split of the data between partners is label agnostic, but it is not he case of the shuffling/corruption |
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Currently most of the functions work with the assumptions that the labels are one-hot-encoded vectors.
Besides the fact that it is not responsive, sometime we need to play with label index. (first label is indexed 1, second label 2, and so on)
A solution can be to add (automatically) at the dataset generation a dict of label, where the keys would be integer and the values would be the vectors for instance.
An instance with MNIST :
dataset.dic_label = { 0: [1,0,0,0,0,0,0,0,0,0],
1 : [0,1,0,0,0,0,0,0,0,0],
2 : [0,0,1,0,0,0,0,0,0,0],
3 : [0,0,0,1,0,0,0,0,0,0],
4 : [0,0,0,0,1,0,0,0,0,0],
5 : [0,0,0,0,0,1,0,0,0,0],
6 : [0,0,0,0,0,0,1,0,0,0],
7 : [0,0,0,0,0,0,0,1,0,0],
8 : [0,0,0,0,0,0,0,0,1,0],
9 : [0,0,0,0,0,0,0,0,0,1]}
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