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?

what other metrics can i use to estimate quality of the model predicting income range - interval estimation task?

Data Science Asked by wando on March 19, 2021

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

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?

Get help from others!

Recent Answers