2
votes
2answers
42 views

The size of the sample for split validation

At this moment I have a dataset with 4000 samples (50% positive and 50% negative). Normally I would do cross validation for this approach, however besides normal data mining techniques I am also ...
1
vote
2answers
81 views

Model instability in data mining. When it is big enough to discredit a model and how to measure it?

Let's say I have two models. One has cumulative lift on test data 4.322578, second 2.84488. The only advantage of the second over the first consists in the quality of having the cumulative lift curve ...
1
vote
0answers
545 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 ...
24
votes
2answers
3k views

How to draw valid conclusions from “big data”?

"Big data" is everywhere in the media. Everybody says that "big data" is the big thing for 2012, e.g. KDNuggets poll on hot topics for 2012. However, I have deep concerns here. With big data, ...
4
votes
1answer
1k 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 ...