我有以下10次实施,我使用UCI Machine learning发布的数据集,这是数据集的链接:
Here are my dimensions
x =
data: [178x13 double]
labels: [178x1 double]
这是我得到的错误
Index exceeds matrix dimensions.
Error in GetTenFold (line 33)
results_cell{i,2} = shuffledMatrix(testRows ,:);
这是我的代码:
%Function that accept data file as a name and the number of folds
%For the cross fold
function [results_cell] = GetTenFold(dataFile, x)
%loading the data file
dataMatrix = load(dataFile);
%combine the data and labels as one matrix
X = [dataMatrix.data dataMatrix.labels];
%geting the length of the of matrix
dataRowNumber = length(dataMatrix.data);
%shuffle the matrix while keeping rows intact
shuffledMatrix = X(randperm(size(X,1)),:);
crossValidationFolds = x;
%Assinging number of rows per fold
numberOfRowsPerFold = dataRowNumber / crossValidationFolds;
crossValidationTrainData = [];
crossValidationTestData = [];
%Assigning 10X2 cell to hold each fold as training and test data
results_cell = cell(10,2);
%starting from the first row and segment it based on folds
i = 1;
for startOfRow = 1:numberOfRowsPerFold:dataRowNumber
testRows = startOfRow:startOfRow+numberOfRowsPerFold-1;
if (startOfRow == 1)
trainRows = (max(testRows)+1:dataRowNumber);
else
trainRows = [1:startOfRow-1 max(testRows)+1:dataRowNumber];
i = i + 1;
end
%for i=1:10
results_cell{i,1} = shuffledMatrix(trainRows ,:);
results_cell{i,2} = shuffledMatrix(testRows ,:); %This is where I am getting my dimension error
%end
%crossValidationTrainData = [crossValidationTrainData ; shuffledMatrix(trainRows ,:)];
%crossValidationTestData = [crossValidationTestData ;shuffledMatrix(testRows ,:)];
end
end
答案 0 :(得分:6)
您正在循环1:numberOfRowsPerFold:dataRowNumber
,每次1:x:178
和i
递增。因此,您可以在index out of bounds
上获得results_cell
错误。
获取错误的另一种方法是testRows
选择超出shuffledMatrix
范围的行。
要在发生错误时暂停代码并开始调试,请在执行代码之前运行dbstop if error
。这样编译器在遇到错误时就进入调试模式,你可以在事情搞乱之前检查变量的状态。
(要禁用此调试模式,请运行dbclear if error
。)