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README.md file update #763

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Expand Up @@ -51,6 +51,14 @@ Negative (blue) words indicate atheism, while positive (orange) words indicate c

<img src="https://raw.githubusercontent.com/marcotcr/lime/master/doc/images/images.png" width=200 />

This image visually explains why the model predicted ‘cat’.

Positive contribution pixels (green): Regions that are important for predicting the cat class. In the image, the cat’s body and face are highlighted.

Negative contribution pixels (red): Regions that decrease the probability of the cat class. In the image, part of a dog’s face and body are included.

LIME divides the input image into small regions (superpixels) and measures how the model’s output changes when each region is removed or altered.

## Tutorials and API

For example usage for text classifiers, take a look at the following two tutorials (generated from ipython notebooks):
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