Any quick way to classify large dataset into smaller buckets to get better Linear Regression model for each bucket

clustering
regression

#1

Hi Everyone,

Let’s say my dataset has 26 categorical variables (A1 through A26) and another 5 Numerical variables (X1 through X4, Y1). Also, this dataset is huge.

Normally, using my business knowledge (limited though), I divide this dataset into multiple buckets and regress to explain Y1~X1 to X4 for each bucket. If the Adjusted R-Square is poor, I plot the data points in tableau to see if X1 to X4 exhibits a patter against Y1. If I see a pattern, then I break down X1 into intervals (that creates more independent variables). Most of the time, I manually slice and dice the data and re-run the regression incorporating changes to the regression equation using my manual findings.

My questions are as follows:

Objective: To predict Y1 for the large dataset using the independent variables X1 to X4.

My Question:
Is there a technique/algorithm to segment the large dataset using the categorical variables A1 to A26 ?(maybe not every column has to be input. with a bit of glance, I can rule out 50% of them non-usable)

Also, If you encounter such task, how would you generally go about it (Just trying to pick your brains on it)

Thanks in Advance,
SRAMS