func getInitialPopulation() []*ng.Cortex {
population := make([]*ng.Cortex, 0)
// create 30 of these
for i := 0; i < 30; i++ {
cortex := ng.XnorCortexUntrained()
// cortex := ng.XnorCortex()
population = append(population, cortex)
}
return population
}
func RunStochasticHillClimber() {
ng.SeedRandom()
// training set -- todo: examples := ng.XnorTrainingSamples()
examples := ng.XnorTrainingSamples()
// create netwwork with topology capable of solving XNOR
cortex := ng.XnorCortexUntrained()
// verify it can not yet solve the training set (since training would be useless in that case)
verified := cortex.Verify(examples)
if verified {
panic("neural net already trained, nothing to do")
}
shc := &nv.StochasticHillClimber{
FitnessThreshold: ng.FITNESS_THRESHOLD,
MaxIterationsBeforeRestart: 2000,
MaxAttempts: 2000,
WeightSaturationRange: []float64{-100 * math.Pi, 100 * math.Pi},
}
cortexTrained, _, succeeded := shc.TrainExamples(cortex, examples)
if !succeeded {
panic("could not train neural net")
}
// verify it can now solve the training set
verified = cortexTrained.Verify(examples)
if !verified {
panic("could not verify neural net")
}
logg.LogTo("DEBUG", "trained cortex: %v", cortexTrained)
logg.Log("done")
}