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docs/userguide/insights.md

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@@ -79,7 +79,9 @@ insight.plot("beeswarm", new_measurements)
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The `force` plot type requires the user to additionally select which single data point
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they want to visualize by specifying the corresponding `explanation_index`:
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~~~python
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insight.plot("force", explanation_index=3) # plots the force analysis of the measurement at index 3
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insight.plot(
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"force", explanation_index=3
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) # plots the force analysis of the measurement at positional index 3
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~~~
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![SHAP_Force](../_static/insights/shap_force.svg)
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@@ -92,7 +94,9 @@ mechanics, we refer to the [SHAP documentation](https://shap.readthedocs.io/en/l
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The explainer can be changed when creating the insight:
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~~~python
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insight = SHAPInsight.from_campaign(campaign, explainer_cls="KernelExplainer") # default explainer
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insight = SHAPInsight.from_campaign(
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campaign, explainer_cls="KernelExplainer"
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) # default explainer
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~~~
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### Experimental and Computational Representations
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[MAPLE](https://papers.nips.cc/paper_files/paper/2018/hash/b495ce63ede0f4efc9eec62cb947c162-Abstract.html)
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variants. For example:
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~~~python
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insight = SHAPInsight.from_campaign(campaign, explainer_cls="LimeTabular", use_comp_rep=True)
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insight = SHAPInsight.from_campaign(
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campaign, explainer_cls="LimeTabular", use_comp_rep=True
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)
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insight.plot("bar")
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~~~
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![SHAP_Bar_Lime](../_static/insights/shap_bar_lime.svg)

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