Structure of Strings

Jay
2011 7 11
2 个回答
回答已采纳
7 次查看（30 天）

0 个投票

Hi!
I want to specify possible parameters for the naive bayes classifier. For this reason, I have created a structure with a field for each parameter and a matrix with possible values.
bayesPosParams.distribution = ['normal'; 'kernel'];
bayesPosParams.prior = ['empirical'; 'uniform'];
bayesPosParams.KSWidth = 'scalar';
bayesPosParams.KSSupport = ['unbounded'; 'positive'];
Unfortunately that does not work: ??? Error using ==> vertcat CAT arguments dimensions are not consistent.
All Strings need to have the same length. What would be the best possibility to specify the parameters nice and consistently?
Thanks in advance, Jay

请先登录，再回答此问题。

 采纳的回答

Andrei Bobrov
Andrei Bobrov 2011-7-11

2 个投票

bayesPosParams.distribution = {'normal'; 'kernel'};
bayesPosParams.prior = {'empirical'; 'uniform'};
bayesPosParams.KSWidth = 'scalar';
bayesPosParams.KSSupport = {'unbounded'; 'positive'};

更多回答（1 个）

Jay
Jay 2011-7-11

1 个投票

Hi Andrei!
Then every field would be a cell array, correct? What's the differences between this approach and using, my just discovered method, bayesPosParams.distribution = char('normal', 'kernel')?
I will want to operate on bayesPosParams with for-loops.
Thanks!

6 个评论
显示 4更早的评论 隐藏 4更早的评论

Jan
Jan 2011-7-11
Using CHAR creates a rectangular matrix by padding shorter strings with spaces. Then comparing a row of the matrix with STRCMP is harder, because the trailing spaces have to be considered. Therefore the cell string is more comfortable and more efficient:
CHAR: unblank(bayesPosParams.distribution(i, :))
CELLSTRING: bayesPosParams.distribution{i}
Andrei Bobrov
Andrei Bobrov 2011-7-11
Thanks Jan, I full agree with Jan
Jay
Jay 2011-7-11
hi, thanks a lot!
If I'd do:
for dis = bayesPosParams.distribution
then dis would become 1x1 cellarrays ( {normal} and {kernel} ) right?
How can I get dis to get the two chararrays 'normal' and 'kernel'?
Thanks again,
Jay
Andrei Bobrov
Andrei Bobrov 2011-7-12
no, dis would become 2x1 cellarrays
>> dis = bayesPosParams.distribution
dis =
'normal'
'kernel'
>> dis{1} % call char array
ans =
normal
>> dis{2} % call char array
ans =
kernel
Jay
Jay 2011-7-12
right, i want to test all possible combinations of parameters.
only way i could think of is to do this with four nested for-loops. Probably very slow, but don't know how to do that else.
So I would for example want to iterate over all chararray-values of bayesPosParams.distribution, namely 'normal' and 'kernel'.
How do I do that?
Something like:
for dis = bayesPosParams.distribution{}
....
but this does not seem right either...
Andrei Bobrov
Andrei Bobrov 2011-7-12
dis - cell array, and may be any operation with 'dis', as with cellarrays

请先登录，再进行评论。

类别

在 帮助中心 和 File Exchange 中查找有关 Creating and Concatenating Matrices 的更多信息

产品

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by