Tagged Questions

1
vote
0answers
141 views

Validation error less than training error — implications?

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 ...
2
votes
1answer
68 views

Is a different CV arrangement the same as a validation set?

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 ...
2
votes
2answers
279 views

What are acceptable validation or cross validation error rates?

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 ...
1
vote
1answer
294 views

How to select validation data when training a neural network?

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 ...
12
votes
3answers
7k views

What is the difference between test set and validation set?

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 ...
4
votes
1answer
642 views

Best practices for measuring and avoiding overfitting?

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 ...