Jump to content

Recommended Posts

Hi All,

I'm working on some data , wherein i have 6 Independent variable and 1 dependent variable.

while running the Regression model on this data, i get very less Accuracy of model as mentioned in below screenshot.


Note :- As far as data Pre-processing is concern , i have scale the features and also imputes the missing values on the basis of mean imputation.

Do let me know if there's any pre-processing feature is there in seek to deal with data.



JItesh Vachheta


Edited by Jitesh Vachheta
For Missing Tag
Link to comment
Share on other sites

  • Seeq Team


Seeq offers a number of functions for cleansing data before it is used in a regression model. This can be an important step because bad data has a negative impact on regression quality as you are observing. Without seeing the raw data it's hard for me to assume what type of cleansing is most appropriate.

There are a couple posts already on Seeq.org you might find interesting:

To see a full list of Signal Cleansing options checkout the Formula documentation in Seeq by selecting Signal Cleansing as seen in the screenshot below. In addition, my screenshot shows an example of agileFilter(). This is one of my go-to functions for smoothing data before subsequent use in other analysis.



If you feel comfortable sharing what your raw data looks like (either a description or screenshot), then I can give you more specific advice.

Cheers, Krista

Link to comment
Share on other sites

Create an account or sign in to comment

You need to be a member in order to leave a comment

Create an account

Sign up for a new account in our community. It's easy!

Register a new account

Sign in

Already have an account? Sign in here.

Sign In Now
  • Create New...