New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Methods to implement dimension reduction techniques. #480

Open

VijaySingh-GSLab opened this issue Oct 5, 2018 · 0 comments

VijaySingh-GSLab commented Oct 5, 2018

We can add some utilities to give user the options to reduce the dimensions of data. For example:

Backward elimination technique
Forward elimination technique
PCA

Advantages of adopting dimension reduction techniques:

It reduce the size of data so ML algorithms run faster.
Avoid over fitting of model
Helps in finding out which columns are significant and which are not.
In few case model accuracy also increases.
Help in visualizing multi-dimensional data.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment