Supervised learning algorithms need a training set and a test set. This snippet show two ways to generate train/test sets. First is by count, where it will take a random number of rows from the Frame and generate two new frame of the specified size. This is useful if you have a very large dataset, but you only want to explore your learning algorithm on a small subset. Second is by ratio, this will break the frame into two parts based on the ratio given. For example you might want to train on 25% of your data, then test on the other 75%.
2 people like thisPosted: 10 years ago by tonyabell
A simple example that creates a frame from a list of dictionaries. Each dictionary is treated as a row that maps column keys to values. The trick is to use Deedle value expansion.
1 people like thisPosted: 10 years ago by Tomas Petricek
Tomas has released their F# data analysis library called Deedle, I just got around to playing with it. It looks really cool!
4 people like thisPosted: 10 years ago by Joel Huang
Some bare-bones example code of inserting a Deedle frame into excel. Adapted from https://github.com/tpetricek/Documents/blob/master/Talks%202013/FsLab%20Showcase%20%28Seattle%29/code/Excel/Excel.fsx
3 people like thisPosted: 9 years ago by Kristian Schmidt