Using the code provided below, modify it to be a neural network that predicts th

Question

Using the code provided below, modify it to be a neural network that predicts the stock market for the next 7 days.

Explanation / Answer

#include #include #include typedef int BOOL; typedef int INT; typedef double REAL; #define FALSE 0 #define TRUE 1 #define NOT ! #define AND && #define OR || #define MIN_REAL -HUGE_VAL #define MAX_REAL +HUGE_VAL #define MIN(x,y) ((x)(y) ? (x) : (y)) void NormalizeSunspots() { INT Year; REAL Min, Max; Min = MAX_REAL; Max = MIN_REAL; for (Year=0; YearEta = 0.05; Net->Gain = 1; NormalizeSunspots(); TrainErrorPredictingMean = 0; for (Year=TRAIN_LWB; YearOutput[i]; Err = Target[i-1]-Out; Net->OutputLayer->Error[i] = Net->Gain * Out * (1-Out) * Err; Net->Error += 0.5 * sqr(Err); } } void BackpropagateLayer(NET* Net, LAYER* Upper, LAYER* Lower) { INT i,j; REAL Out, Err; for (i=1; iUnits; i++) { Out = Lower->Output[i]; Err = 0; for (j=1; jUnits; j++) { Err += Upper->Weight[j][i] * Upper->Error[j]; } Lower->Error[i] = Net->Gain * Out * (1-Out) * Err; } } void BackpropagateNet(NET* Net) { INT l; for (l=NUM_LAYERS-1; l>1; l--) { BackpropagateLayer(Net, Net->Layer[l], Net->Layer[l-1]); } } void AdjustWeights(NET* Net) { INT l,i,j; REAL Out, Err, dWeight; for (l=1; lUnits; i++) { for (j=0; jLayer[l-1]->Units; j++) { Out = Net->Layer[l-1]->Output[j]; Err = Net->Layer[l]->Error[i]; dWeight = Net->Layer[l]->dWeight[i][j]; Net->Layer[l]->Weight[i][j] += Net->Eta * Err * Out + Net->Alpha * dWeight; Net->Layer[l]->dWeight[i][j] = Net->Eta * Err * Out; } } } } void SimulateNet(NET* Net, REAL* Input, REAL* Output, REAL* Target, BOOL Training) { SetInput(Net, Input); PropagateNet(Net); GetOutput(Net, Output); ComputeOutputError(Net, Target); if (Training) { BackpropagateNet(Net); AdjustWeights(Net); } } void TrainNet(NET* Net, INT Epochs) { INT Year, n; REAL Output[M]; for (n=0; n

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