Generative Model, Walkthrough, Data Science.
class_params.items(): mean = params['mean'] std = params['std'] x_holder[class_name] = np.random.normal( loc=mean, scale=std, size=(int(100*params['pC']), 3) ) y_label = class_name.strip()[-1] y_holder.extend([y_label]*int(100*params['pC'])) x_train = np.concatenate( [x_holder['Class 1'],