I have 32 samples each for 12 different experiments. They contain 4 variables (1 dependent and 3 independent). I want to artifical neural networking and compare the results with the previously performed correlation analysis using R analysis.
What should I do? Should I consider all variables as dependent or is thr any way to apply neural networking easily on such data?
Kind regards
Haibat Ali
Applying neural network on small dataset having only 4 variables, makes no sense.
Although this dataset is quite small, in general the dataset should be split into two main sub-samples comprising training and testing sub-samples. The dependent parameter can be estimated by means of the independent parameters.
Dear Haibat Ali ,
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Regards,
Shafagat
While this sample is very minimal, the dataset can typically be divided into two main sub-samples, containing inter-samples for training and certification. With the independent parameters, the dependent parameter can be calculated.
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