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Because the current rule of thumb is that ~9/10 startups fail. If you can reduce that to a 50/50 bet, you've made quite an improvement.
by adwf 12y ago
Because the current rule of thumb is that ~9/10 startups fail. If you can reduce that to a 50/50 bet, you've made quite an improvement.
- mojuba 12y agoNot really. What the article says is, the model would predict 50% of time whether a company will fail or not, which doesn't make sense, because 50% for a binary prediction (i.e. fail or not) is exactly nothing. So maybe it's just bad or confusing wording in the article, the guy actually meant to say something else.
- adwf 12y agoYeah I'm going with confusing wording, I think he meant what I said above. Not to mention he could be referring to eliminating false positives, which is slightly different to finding true positives versus true negatives.
- mox1 12y agoI think it's easier to relate to a coin flip if we use an "unfair coin". 90% of the time the coin flip returns tails (aka fail). 10% of the time it returns heads (aka win). For a given coin flip, their algorithm can predict the results 50% of the time. At this point I don't remember the calculations off the top of my head, but it involves a Binomial distribution.