I am running a neural net to predict used car prices, sample size is 800. Using both 10-fold cross validation (10 times) and 1/3 holdback (10 times), the $R^2$ for training is about 0.60 and for ...
I have a smallish dataset ~ 1500 rows X 500 columns. I've been using a standard 5 fold CV setup where row 1 = CV set1, row2 = CV set2, ... row 6 = CV set1,etc. I'm at the point where I'm trying to ...
Is there a commonly acceptable error rate for validation? As in, if the error rate is less than X %, then my machine learning method would be considered "successful". I'm looking for something ...
I am training a neural network with time dependent financial data. In order to avoid overfitting I would like to stop the training at the point where my neural network stops improving on a set of ...
I found this confusing when I use the neural network toolbox in Matlab. It divided the raw data set into three parts: training set validation set test set I notice in many training or learning ...
I am developing automated trading systems for the stock market. The big challenge has been overfitting. Can your recommend some resources describing methods for measuring and avoiding overfitting? I ...