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发帖数: 273 | 1 【 以下文字转载自 Statistics 讨论区 】
发信人: myregmit (myregmit), 信区: Statistics
标 题: Predict values of vectors by other vectors generated by black box
functions
发信站: BBS 未名空间站 (Sun Mar 2 11:38:56 2014, 美东)
Hi,
I need to solve a problem about predicting values of some numerical vectors
by using other numerical vectors with all these vectors in the same vector
set, which is generated by one or more black box functions.
Given a vector space:
P =[S_1, S_2, …, S_T | Sk is a vector of q numbers, k = 1, ..., T]
Find a sub-group of vectors g = {S_d | d belongs to 1, …, T } and a
function h( S_d )
Such that
Difference between the value of h(S_g) and S_r is minimized
set g + set r = set P
set g and set r have no overlap
The question can also be expressed as:
Given a set S of vectors, find a function h() whose arguments are from part
of vectors of S (we call it S1). The output of h() are the vectors of
another part of S (we call it S2). The output values of h() are the
predicated values for S2. We need to keep the prediction errors minimized
and the size of S1 minimal.
Questions:
How to find the h() ?
What kinds of knowledge I need to solve the problem ?
Any help would be appreciated.
Thanks |
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