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Planning the phase 1 changes.
Published:
When adding functionality to an existing script, the best practice is to add, debug and test each new feature on it's own.
Since my script is modular and responds to the number of columns imported from the csv history file, the function will be modified to add each feature, starting with the most recent appearance of each digit in the distribution. Using pure frequency, there are frequent ties that were in need of a way of being broken.
The second pass will print the P value of the chi-square goodness of fit test for the 150 draws in the current run.
So using version control, the main code will be branched to implement each change and only rolled back into the main code when working. This way I always maintain a WORKING copy to roll back to in the event of errors.
Phase 2 will be a clean sheet implementation, therefore will take much longer to plan and code.
No shortage of work in this hobby!
Comments
Frequency has a many to many relationship... when focusing on entity relationships, each digit will have it's own frequency, but the digits may share frequencies, such as 0, 4, 7 and 9 all having a frequency of 9.33%
A recency number would, in a column, be a one to one, as multiple digits cannot appear on the same draw, each of the digits will have a unique row_of_last_appearance.
Then it becomes important to determine which feature carries more weight, and if it matters on the closest last appearance.
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