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tree encoding logic #6

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Sandy4321 opened this issue Apr 6, 2020 · 3 comments
Open

tree encoding logic #6

Sandy4321 opened this issue Apr 6, 2020 · 3 comments

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@Sandy4321
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can you share how to understand tree encoding logic
for example what does it mean:
leaves_c
[(1,), (-7, -1), (-3, -1, 7), (-12, -1, 3, 7), (-1, 3, 7, 12)]

thanks

@Sandy4321
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dic for this is
leaves_c
[(1,), (-7, -1), (-3, -1, 7), (-12, -1, 3, 7), (-1, 3, 7, 12)]
dic
{1: 11, 2: 8, 3: 7, 4: 6, 5: 4, 6: 5, 7: 3, 8: 0, 9: 2, 10: 9, 11: 1, 12: 10}

@Sandy4321
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x.shape
(691, 12)

@Sandy4321
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may be
for this encoding
leaves_c
[(1,), (-7, -1), (-1, 7, 12), (-12, -3, -1, 7), (-12, -1, 3, 7)]

we have
1 yes
1no to 7no
1no to 7yes to 12yes
1no to 7yes to 12no to 3no
1no to 7yes to 12no to 3yes
per
slide #12
https://github.com/xiyanghu/OSDT/blob/master/doc/NeurIPSSlides.pdf

where
dic
{1: 11, 2: 8, 3: 7, 4: 6, 5: 4, 6: 5, 7: 3, 8: 0, 9: 2, 10: 9, 11: 1, 12: 10}
is encoding from node number to actual feature number?

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