How can i randomly divide a dataset(matrix) into k parts ??

10 次查看(过去 30 天)
I have a database and i want to randomly divide it into ka parts of equal size . if the database has n row each part will contain n/k randomly chosen row from the dataset .

采纳的回答

Mariem Harmassi
Mariem Harmassi 2012-9-11
编辑:Oleg Komarov 2012-9-11
function [idxo prtA]=randDivide(M,K)
[n,m]=size(M);
np=(n-rem(n,K))/K;
B=M;
[c,idx]=sort(rand(n,1));
C=M(idx,:);
i=1;
j=1;
ptrA={};
idxo={};
n-mod(n,K)
while i<n-mod(n,K)
prtA{j}=C(i:i+np-1,:);
idxo{i}=idx(i:i+np-1,1);
i=i+np;
j=j+1;
end
prtA{j}=C(i:n,:);
end
this a my algo it works very well think u for ur answers

更多回答(2 个)

Oleg Komarov
Oleg Komarov 2012-9-9
编辑:Oleg Komarov 2012-9-9
Suppose you have the N by M matrix A. I would randomly permute positions from 1:N and then group them into k partitions. Follows the code.
% Sample inputs
N = 100;
A = rand(N,2);
% Number of partitions
k = 6;
% Scatter row positions
pos = randperm(N);
% Bin the positions into k partitions
edges = round(linspace(1,N+1,k+1));
Now you can "physically" partition A, or apply your code to the segments of without actually separating into blocks.
% Partition A
prtA = cell(k,1);
for ii = 1:k
idx = edges(ii):edges(ii+1)-1;
prtA{ii} = A(pos(idx),:); % or apply code to the selection of A
end
EDIT
You can also avoid the loop, but in that case you have to build a group index that points the row to which partition it belongs and then apply accumarray() to execute your code on the partitions.
  4 个评论
Mariem Harmassi
Mariem Harmassi 2012-9-10
Yes i tried it but prtA =
[17x2 double]
[17x2 double]
[17x2 double]
[17x2 double]
[16x2 double]
[16x2 double]
and what i want is all the result that i expect is
prtA =
[17x2 double]
[17x2 double]
[17x2 double]
[17x2 double]
[17x2 double]
[15x2 double]
all the partition with the same size and the rest in the last partition
HOw to do that
Oleg Komarov
Oleg Komarov 2012-9-11
Adapting to your requests, I build edges in a slightly different way then:
% Sample inputs scrambling
N = 100;
A = rand(N,2);
k = 6;
pos = randperm(N);
% Edges
edges = 1:round(N/k):N+1;
if numel(edges) < k+1
edges = [edges N+1];
end
% partition
prtA = cell(k,1);
for ii = 1:k
idx = edges(ii):edges(ii+1)-1;
prtA{ii} = A(pos(idx),:);
end

请先登录,再进行评论。


Azzi Abdelmalek
Azzi Abdelmalek 2012-9-9
编辑:Azzi Abdelmalek 2012-9-10
A=rand(210,4);[n,m]=size(A);
np=20;B=A;
[c,idx]=sort(rand(n,1));
C=A(idx,:);
idnan=mod(np-rem(n,np),np)
C=[C ;nan(idnan,m)];
[n,m]=size(C);
for k=1:n/np
ind=(k-1)*np+1:k*np
res(:,:,k)=C(ind,:)
end
idxo=reshape([idx ;nan(idnan,1)],np,1,n/np) % your original index
  9 个评论
Mariem Harmassi
Mariem Harmassi 2012-9-11
Yes i see that , :((( so itsn't useful for my problem because i need to keep the initial configuration the matrix is dataset of objects so i can t change the column into rows what reshape do a column is descriptor.

请先登录,再进行评论。

类别

Help CenterFile Exchange 中查找有关 Matrix Indexing 的更多信息

Community Treasure Hunt

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

Start Hunting!

Translated by