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Hey there Ronald... This reminds me of something I did a number of years ago for equities. My set-up was essentially a generalization of the same idea you are working with. The way I generalized the approach was that rather than trying to egorize candles into traditional patterns (long, doji, short, etc.) and then match sequences, I just generated sequences of percentage-based differentials for each of OHLC on each bar, as compared to the previous bar. By expressing all of these values from bar to bar in terms of similarity to the previous...
That's an interesting approach Theo, I did something similar with a coordinate-based system. Each individual bar is given 3 coordinates. Those coordinates can be plotted in a 3-D region. The next step is finding a way to group those bars so bars within a specific coordinate region are identified as the same bar. It's this last step where I'm having trouble. Theoretically, I could expand this coordinate system to as many dimensions as I could possibly want. But, before I can do that, I need to figure out how to combine various groups together. If you know anyone who is good with clustering algorithms, I would love to speak with them.