Skip to content
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

Add more info on working with categorical data #16881

Merged
merged 13 commits into from
Feb 12, 2020
Merged

Add more info on working with categorical data #16881

Changes from 1 commit
Commits
Show all changes
13 commits
Select commit Hold shift + click to select a range
106f98b
Add feature label article
natke Jan 28, 2020
a87478d
Add one hot encoding
natke Jan 29, 2020
57b3e24
Added one hot encoding and hashing to data prep how-to
natke Jan 29, 2020
b47c2ae
Acrolinx and tidy up
natke Jan 29, 2020
65105ad
Fix xref
natke Jan 29, 2020
d1245e5
Fix typo
natke Jan 29, 2020
61e9eb4
Remove one-hot encoding example, as the example is in the API docs
natke Feb 6, 2020
647091c
Update docs/machine-learning/how-to-guides/prepare-data-ml-net.md
natke Feb 11, 2020
600d8c3
Update docs/machine-learning/how-to-guides/prepare-data-ml-net.md
natke Feb 11, 2020
1b42d38
Update docs/machine-learning/how-to-guides/prepare-data-ml-net.md
natke Feb 11, 2020
e64cc4c
Update docs/machine-learning/how-to-guides/prepare-data-ml-net.md
natke Feb 11, 2020
781166b
Made tenses consistent for loading enmerable data
natke Feb 11, 2020
64c0352
Update after review
natke Feb 12, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
Update docs/machine-learning/how-to-guides/prepare-data-ml-net.md 
Co-Authored-By: Luis Quintanilla <[email protected]>
  • Loading branch information
@natke @luisquintanilla
natke and luisquintanilla committed Feb 11, 2020
commit 647091c14159c13316ba7d21c75bb9169b08edc5
2 changes: 1 addition & 1 deletion docs/machine-learning/how-to-guides/prepare-data-ml-net.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -182,7 +182,7 @@ The result of binning creates bin bounds of `[0,200000,Infinity]`. Therefore the

## Work with categorical data

One of the most common types of data is categorical data. Categorical data has a finite number of categories. For example, the states of the USA, or a list of the types of animals found in a set of pictures. Whether the categorical data are features or labels, they must be mapped onto a numerical value in so that they can be used to generate a machine learning model. There are a number of ways of working with categorical data in ML.NET, depending on the problem you are solving.
One of the most common types of data is categorical data. Categorical data has a finite number of categories. For example, the states of the USA, or a list of the types of animals found in a set of pictures. Whether the categorical data are features or labels, they must be mapped onto a numerical value so they can be used to generate a machine learning model. There are a number of ways of working with categorical data in ML.NET, depending on the problem you are solving.

### Key value mapping

Expand Down