Time for the next approach... Machine Learning!


The current deep dive has led to some hypotheses I would like to experiment with.

The lottery is definitely laid out like a time series problem, list of dates with data for each. The problem with time series is it uses moving averages, never gives a clean prediction... enter classifiers... look at the numbers as categories without math properties!

I am still weeks away from usable code, but here is the plan. Use time series analysis for classifiers with an LSTM (long short term memory) in 2 layers... splitting the data 80% training, 20% validation to construct the model, then forecast for 7 days (since the run time will be in hours, not seconds).

This time even more modularity. Last system (followers) had 18 modules, one for each position of the pick 3/4/5 mid and eve... this one will have but one!! Every change to the old system required doctoring 18 instances of the function code.

This begins the introduction of "features" to the data, namely odd even to split the numbers into 0,2,4,6,8 and 1,3,5,7,9 and added to that high and low, splitting the numbers into 0,1,2,3,4 and 5,6,7,8,9.

The example is one, 

Value = 1, E=0, L=1

E is a binary value, 1 = even, 0 = odd

L is a binary value, 1 = low group, 0= high group

These will be included in the evaluation by a method called "one hot encoding", which uses binary feature information to help find patterns.

A 2 layer LSTM has a better shot at finding difficult patterns, while a 3 layer LSTM is overkill and may induce bias and over fitting. For reference, a one layer LSTM does not do as well with complex patterns in a sequence.

This is my actual first step in machine learning, months before I get to take a college class in it, so the time will not be wasted regardless the results. Found a win win!

Along with this will be learning seaborn and matplotlib to graph out data.

All of this came from a starter chat with ChatGPT about pattern matching and the difference between prediction and forecasting.

Next big thing? Doubtful but always optimistic until the first live test results. A positive step in coding? Absolutely!

Entry #234


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