DislikedSince we have both NN (100 examples, 3 inputs, 500 cycles per training) and SVM (145 examples, 20 inputs) models with decent results (the first a regression model and the second a classification model). It's cool to attempt to build an ensemble of the two models and see if we can improve our results. This means retraining both models on each bar and simply only acknowledging a long signal when both say "go long" and a short signal when both say "go short" (do nothing if they disagree). We build a model ensemble using both classification and regression,...Ignored