
Ask HN: Dumb Machine Learning question – how to get insights, not predictions? - thenomad
I&#x27;ve been trying to dig into ML and figure out the answer to this question, but so far I&#x27;m repeatedly and enthusiastically hitting brick walls. So I thought I&#x27;d ask the assembled brains here.<p>Say I have a large corpus of data on, say, esport teams&#x27; makeup and performance, along with whether they won or not. (Or alternatively, visitors to a website and whether or not they converted, or whatever.)<p>I&#x27;ve got about 10-20 different fields describing each team - what heroes they picked, what they did in the game, etc - and then a binary win&#x2F;loss.<p>I know how to train an ML model to predict whether a team will win based on that data.<p>But how do I use an ML model to extract insights about what makes a team <i>more likely to win</i>? Stuff like &quot;if 3 people picked these 3 heroes and then 1 person went to this location on the map, there&#x27;s a 75% chance that the team wins&quot;?<p>I can find data visualisers allowing humans to pick through data and look for trends, but I can&#x27;t find a way to get a machine to do it. And I&#x27;m sure I&#x27;m missing something really obvious here.<p>So - is this doable with ML techniques, and if so, how would you do it?
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pizza
related: [http://www.darpa.mil/program/explainable-artificial-
intellig...](http://www.darpa.mil/program/explainable-artificial-intelligence)

I think you are probably asking for something far more advanced than
prediction of a simple numerical model?

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maieuto1
There is a deep and important difference between a reliable prediction and an
actual explanation.

