CODEWITHSUNDEEP
pythonpandasmachine-learningcross-validationboosting
CodeTry
CodeTry

Reputation: 312

int vs Float in regression modeling

This is general question to understand a concept.

I have a dataframe with all columns having float values(precision varies from 2 to 8 digits).

I use GBM to train my model. When i train my model with all float values - r2 score -0.78

Same when all columns are converted to integer values - r2 score -0.72

Why does r2 score drop when float is converted to integer ?

Is it something very specific to my data or in general is it expected to drop ?

Upvotes: 0

Views: 1555

Answers (1)

Anurag Reddy
Anurag Reddy

Reputation: 1215

The problem in your case is that you might be losing resolution while converting to integers. A good metric would be to measure the quantization or rounding error in your inputs while converting from float to integers. This link has a very basic explanation for rounding error. Rounding error might be a useful metric to compare the accuracy drop with respect to precision and number systems.

Upvotes: 1

Related Questions