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I trained a model that predicts customer's income given the features:

  • age, declared income
  • number of oustanding instalment, overdue total amount
  • active credit limit, total credit limit
  • total amount

The output is a prediction: lower-upper bound for a customer: e.g. [8756-9230]

Metrics used:

  • NIRDM - not in range distance mean - how far the value is from the closest bound (on average) for values out of range(similar to true negative)
  • in-interval - percent of tested values that actually happen to be within the range(similar true positive)

e.g. NIRDM = 1.37, on avg values deviate by 0.37, less is better.

my question: what other metrics can be used to estimate the accuracy of the model.

I dont have deeper expertise on this 'range estimation task', maybe confidence interval?

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