| --- Log opened Sat Jan 14 00:00:41 2017 | ||
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| mikeling | lisitsyn: wiking hi, what's the difference between left hand side and right hand side features? | 07:49 |
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| mikeling | why we need to define features as left and right hand side ? | 07:50 |
| lisitsyn | mikeling: that's a bit tricky | 13:04 |
| lisitsyn | the thing is that kernels and distances are defined with two arguments | 13:04 |
| lisitsyn | like K(x,x') | 13:04 |
| lisitsyn | so there is the first thing and there is the second thing or left and right | 13:05 |
| lisitsyn | with a bit of strange training requires you to have K(train, train) | 13:05 |
| lisitsyn | so lhs==rhs==train | 13:05 |
| lisitsyn | but when you apply kernel SVM you still need your train set | 13:06 |
| lisitsyn | in this case it becomes K(train, test) | 13:06 |
| lisitsyn | because you're comparing train examples with test examples | 13:06 |
| mikeling | lisitsyn Oh sorry, I just afk for a while, forget to change me irc status to afk..... | 14:06 |
| mikeling | but how about the situation in KNN, what's the meaning of lhs and rhs in https://github.com/shogun-toolbox/shogun/blob/develop/src/shogun/multiclass/KNN.cpp#L141 | 14:13 |
| mikeling | furthermore, if we only separate features as lhs and rhs, how could we deal with the numbers of features? | 14:14 |
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| mikeling | lisitsyn: Hmmm, As to KNN, If I have a sample named x1 and can been represented as a 4 dimensions vector like <1, 3, 4, 5>, so when I want to use a data set (x2, x3, x4, x5.... which also are 4 dimensions vectors) to classify x1, which is the lhs feature and which are rhs features? | 15:04 |
| mikeling | x1 == lhs and x2 == rhs ? | 15:04 |
| mikeling | lisitsyn: Shogun is the first ML tool box I used, so I need to learn some more things to get used it :) | 15:08 |
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| --- Log closed Sun Jan 15 00:00:42 2017 | ||
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