The error you're encountering arises because trainNetwork expects the input table for classification with numeric features to follow a specific structure:
- First column: a cell array where each cell contains a 1×m numeric row vector (the features)
- Second column: a categorical array representing the labels
To fix your issue, you can convert the numeric feature matrix X into a cell array using num2cell(X,2) and convert the label vector Y into a categorical array. Then construct the table like this:
predictorCell = num2cell(X, 2);
Ycategorical = categorical(Y);
tbl = table(predictorCell, Ycategorical, 'VariableNames', {'Predictors','Response'});
Make sure to use this tbl for both training and testing data splits, and remove any one-hot encoding or splitvars logic that’s not needed here.
You can refer to the official MATLAB documentation to learn more about
