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@@ -166,7 +166,7 @@ Thus, the transfer learning models from the ADAPT library can be seen as machine
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The ADAPT library proposes numerous transfer algorithms and it can be hard to know which algorithm is best suited for a particular problem. If you do not know which algorithm to choose, this [flowchart](https://adapt-python.github.io/adapt/map.html) may help you:
|**Quick-Start Plotting Results**. *The dotted and dashed lines are respectively the class separation of the "source only" and KMM models. Note that the predicted positive class is on the right of the dotted line for the "source only" model but on the left of the dashed line for KMM. (The code for plotting the Figure is available [here](https://adapt-python.github.io/adapt/examples/Quick_start.html))*|
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@@ -285,4 +285,4 @@ If you use this library in your research, please cite ADAPT using the following
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This work has been funded by Michelin and the Industrial Data Analytics and Machine Learning chair from ENS Paris-Saclay, Borelli center.
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