[scikit-learn] Run time complexity of algorithms

[Shubham Ashok Gandhi]

Hello,

Hope you guys are doing well.

I needed information on the time complexity of the models under supervised
learning
<http://scikit-learn.org/stable/supervised_learning.html#supervised-learning>
title.
I am looking for this information because- we (my team) are building a
platform that allows a user to run multiple models. The models we select to
build are based on a couple of user requirements such as time, accuracy and
model interpretability. This information will help us in understanding what
models not to select for large datasets and so on.

More specifically, I am looking for information on these algorithms

OLS
Elastic Net
LARS
Bayesian regression
Linear Discriminant Analysis
SVM (all kernels)
Nearest Neighbors regression
Decision Trees
Random Forest
AdaBoost
Gradient Tree Boosting

Let me know if there's additional information or details you need me to
provide

-- 

Regards,

Shubham Ashok Gandhi
Ph: (+91) 8987419771 <089874%2019771>
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