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Pretty banal article. TLDR: A very complicated model will fit simple data, as will a simple model. Modern ML/AI has nothing to do with 1D timeseries forecasting
by stanfordkid 8y ago
Pretty banal article. TLDR: A very complicated model will fit simple data, as will a simple model. Modern ML/AI has nothing to do with 1D timeseries forecasting.
- cs702 8y agoWas about to write the same thing. What the heck is this doing on the front page?
- smus 8y agoHacker news jumps at any opportunity to write off ML
- dang 8y agoPlease don't post unsubstantive comments here.
- henning 8y agoThere have been thousands of papers and many books written on the subject of using machine learning for time series forecasting and an unknown amount of money traded/invested with it. Most of them cast trading as a time series forecasting problem where performance is measured by mean square error. They usually then assume that would lead to profitable trading. You don't get to define what "modern machine learning" is any more than I do. The application of complex models to higher-dimensional domains have problems of their own. Both the successes and failures are worth writing and thinking about. The post is an important reminder about simplicity and complexity in modeling. That's why I submitted it.
- stanfordkid 8y agoI don't understand why I'm being downvoted for this opinion -- the topic of overfitting gets beaten to death by the 3rd week of every intro AI/statistics/ML class out there. I didn't find it very worthy of the frontpage (or a blog post).