This repository demonstrates the usage of hover to understand and supervise a machine learning task.

Pavel

Last update: Dec 3, 2021

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Overview

Hover Example Apps

(works out-of-the-box on Binder)

This repository demonstrates the usage of hover to understand and supervise a machine learning task.

Simple Annotator

use the lasso/tap/poly tool to select data points
assign your labels and hit "Apply"
in a real use case on your computer, "Export" will save a DataFrame
take advantage of the text/regex search box

Linked Annotator

on top of the Simple Annotator, showes another plot which is focused on search
the search boxes are independent across plots, minimizing interference in between
💡 the selections in the plots are synchronized. You can select in one and label in the other!

Active Learning

compared with the Linked Annotator, replaces the left plot with the predictions of a model in the loop
💡 inspect data points based on their prediction confidence and locations!

Snorkel Annotator

compared with the Linked Annotator, replaces the left plot with Snorkel labeling function outputs
in a real use case, you can check the labeling functions and your annotations against each other.
💡 one could also exploit labeling functions as sophisticated "filters" to help find interesting data points!

Comments

Label encoding is bugged in active learning example
This happens when the 'raw' subset of the dataset has a label that the 'dev' subset does not.

SupervisableDataset assumes that labels in the 'raw' subset are irrelevant but those in 'train' are, which is all well and good.

However, it should be made clear how and when annotated data points in 'raw' get committed to 'train'. It should also be clear that there are times when one want to deduplicate 'raw' against 'train' (i.e. to 'lock' those annotated points) and times when one doesn't (i.e. to keep those points open to modification).

these commit and deduplicate' actions shall be accessible as app-level(cross-explorer) widgets.

also need a button to push dataframe updates to explorer sources. This isn't automatic due to performance considerations.. perhaps add a scheduled pull/push from dataframes to sources?

update_population and retrain_model should read the 'train' set rather than the 'raw' set.

bug
opened by phurwicz 1

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This repository demonstrates the usage of hover to understand and supervise a machine learning task.

Related tags

Overview

Hover Example Apps

(works out-of-the-box on Binder)

Simple Annotator

Linked Annotator

Active Learning

Snorkel Annotator

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Comments

Label encoding is bugged in active learning example

Owner

Pavel

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