Open malctaylor15 opened 6 years ago
Use different versions of elastic search and linear regression to reduce the number of variables
After one hot encoding, there are too many variables to choose from.
Find a way to drastically reduce the number of variables and increase the performance of a linear regression.
Some potential ideas:
Use Lasso and Ridge regression to reduce the number of variables to something more managable and that will yield to better results.
Use a stepwise method .. Forward or backwards regression
Look into different linear regression types ... least squares, hinge etc.
More notes to come....
Use different versions of elastic search and linear regression to reduce the number of variables
After one hot encoding, there are too many variables to choose from.
Find a way to drastically reduce the number of variables and increase the performance of a linear regression.
Some potential ideas:
Use Lasso and Ridge regression to reduce the number of variables to something more managable and that will yield to better results.
Use a stepwise method .. Forward or backwards regression
Look into different linear regression types ... least squares, hinge etc.
More notes to come....