<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" xmlns:wfw="http://wellformedweb.org/CommentAPI/">
	<channel>
		<title>I will need to step up my game and make a python gui desktop app</title>
		<link>/blogentry/185820</link>
		<atom:link href="https://www.lotterypost.com/rss/blogcomments/185820" rel="self" type="application/rss+xml" />
		<description>hypersoniq's Blog: I will need to step up my game and make a python gui desktop app</description>
		<dc:language>en-us</dc:language>
		<generator>Lottery Post RSS Generator</generator>
		<item>
			<title>Original Blog Entry: I will need to step up my game and make a python gui desktop app</title>
			<link>/blogentry/185820</link>
			<guid isPermaLink="true">/blogentry/185820</guid>
			<pubDate>Sun, 28 Jul 2024 17:24:27 GMT</pubDate>
			<dc:creator>hypersoniq</dc:creator>
			<description><![CDATA[<p>The visualization script does work to display the last 10 draws for one position. I need to make a program that lets the series be overdrawn for all positions on the same grid, but also toggled to show any particular series (ball 1 etc).<br /><br />Before the fancier equations are applied, I think it would be interesting to rework the existing follower script to find the followers of each vector.<br /><br />The trick is it may take more than one approach to find usable data.<br /><br />The components planned so far...<br /><br />1. A visualization component... this is where it shows the last 10 draws of any pick n game for which it has history... from pick 2 mid to pick 5 eve. Selectable and reading directly from the last 10 entries in the selected draw database. Automating the data import will be a huge difference maker when moving to the larger games.<br /><br />2. A full history analyzer to get a starting point. This will be a simple rework of the follower script but using vectors rather than numbers. Here is where constraints of the grid would be applied. If a 9 was the last number, but the most frequent follower vector has a positive angle, then that can be rejected in favor of the next one on the distribution list that satisfies the constraint.<br /><br />3. Some sort of discovery machine learning algorithm that can work on finding the facts of the distributions.<br /><br />Finishing 1 and 2 will give a workable system, but finishing all 3 would be more helpful in creating a rules-based decision system.<br /><br />Maybe the CS guy should figure out how to post images...<br /><br />Anyway, happy coding!... &#x5b;&#xa0;<a href="/blogentry/185820">More</a>&#xa0;&#x5d;</p>]]></description>
			<category>Blog Entry</category>
			<category>hypersoniq</category>
			<wfw:comment>https://www.lotterypost.com/blogentry/185820</wfw:comment>
		</item>
	</channel>
</rss>

