Hi, I'm trying to create a data set for using it with BackpropTrainer *(PyBrain)*
The model is that i have a bunch of inputs (which can have multiple values). Resulting in some Output Kx( different values). Sample data ( A subset of the data ) Input (x) Input (y) Input (z) Input(a) Output(k) X1 Y1 Z1 A1 K1 X1 Y2 Z2 A3 K2 X2 Y3 Z2 A2 K1 Where Input x can have any of the following value in a specific entry: (X1,X2,x2) *An example from PyBrain Documentation for a simple XOR data set modeling:* >>> ds.addSample((0, 0), (0,))>>> ds.addSample((0, 1), (1,))>>> >>> ds.addSample((1, 0), (1,))>>> ds.addSample((1, 1), (0,)) As the function is simple here (XOR) and the inputs and o/p's can be represented in binary format. How can i model a data set for a slightly complex like mine ? *Please let me know if i mis-speak or interpret something here.* -Prudhvi _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
