Hi All, Wondering about what people think about a DS approach to automation WRT back test fitting. System background: Using ES System can be shown a "pattern" on an intraday chart, out of back test sample range. Pattern is then processed into the "find it" sub system When it is back tested, this "pattern" can be "found" somewhere between 2-4 times over a two year period. With very basic trade management, the win rate can be, 2 for 2, 2 for 3 or 3 for 4. So what would be the problem with finding 20-30 patterns and having the system use that to trade? Patterns can be added and removed. Pattern sets can be selected based on a criteria, of course. So far the only defined sets are Long and Short. Is this really over fitting? In some sense ML and DS are all about "fitting" and not necessarily "over fitting" Obvious points are: Collisions in setups: So far very few. Can't find 20-30 patterns: So far 0-5 patterns per day with mode being 2, mean 2.2. Heavy computing load: Not really an issue. Code is fairly compact and efficient. Need more data for back testing: Working on it. Target is 4-6 years. What is the Win:Loss ratio: About 2.5-3.0: 1 Some people have obviously gone down this path before! Comments?