Stock Market pattern recognition with machine learning


I've started to study statistics and R studio in general, to utilize it in my stock market trading. I dreamed of a market indicator, that analyzes exported data, via R studio (and perhaps h2o, which I am also studying).
The concept is, that I export csv's for 4 different time frames, and 200 observations of numerous variables in each. For each set of this (labeled) data, I want to tell the system that this is a long entry situation, that is a short entry situation, while others are neutral situations, so I want R studio to return the class of the entered data, peridoically. Is there such model? As far as I know, none of the basic models would fit my needs (neither linear/logistic regression, nearest neighbours, K means, decision trees nor SVMs), since these are classification models, but can only return binary values.
Please advise me, where to head to? Did I miss something?

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