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Product managers for ML/AI products need to understand this post.

That confusion matrix is something I have failed to get traction for in the past, but I'd say all market fit will be measured based on the customer's valuation of that matrix vs. the profile of it your product delivers. It doesn't matter what field you are in, this is the metrics framework for every analysis product out there, imo.

e.g. a customer has an expectation of tp/fp tn/fn rates that is valuable for themselves, and your given tech has hard limits on the trade offs between them. The real secret is that the values of the confusion matrix do not apply to whole or most of a customer vertical, but rather to individual customers with similar matrix values across verticals.

I think you can predict when a ML/AI product company will fail because they think they can apply their product to the vertical of their first few customers, making the false assumption that their confusion matrix applies all the way up that vertical - instead of hunting customers with the same matrix values in other verticals.



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