I have a dataset of 19 non linear regression data points. I am training the first 10 and trying to predict the next 9 values using different Neural Network. However, after trying out mulitple Neural Networks such as Radial Basis Function, Baysian Reguralization BackPropogation, Function Fitting Neural Network and LSTM, i am still not getting good prediction results. I have attached the data where X is the input and Y is the output. First 10 data points are being used for training and next 9 points are used for testing. I have also attached by code which uses Baysian Regularization backpropogation.
Attached is the dataset link :
The results obtained using Baysian Regularization backpropogation are shown in graph attached below :
The code used is as follows:
out_col = 2;
inp_col = 1;
n = 7;
Neurons = 5;
XValidation = data(n+1,inp_col);
net = feedforwardnet(Neurons,'trainbr');
[net,tr] = train(net,X_Train',Y_Train');
y = net(XValidation')';
Kindly let me know how can i improve the prediction results?