Data ScientistExplainabilityIntermediateSingle prompt

LIME Explanation AI Prompt

This prompt generates simple local explanations for selected individual predictions using LIME. It is most helpful when stakeholders care about case-by-case reasoning in language that is easy to communicate. The chosen set of examples covers typical, extreme, borderline, and wrong predictions.

Prompt text
Use LIME to explain individual predictions from this model in plain English.

Generate LIME explanations for 5 specific predictions:
1. One very high prediction (top 5% of predicted values)
2. One very low prediction (bottom 5% of predicted values)
3. One borderline prediction (near the decision threshold)
4. The single prediction the model got most wrong
5. A randomly selected typical prediction

For each explanation:
- Show the top 10 features that pushed the prediction up or down
- Display as a horizontal bar chart with green bars (positive contribution) and red bars (negative contribution)
- Write a 2-sentence plain-English explanation: 'The model predicted [value] primarily because [top driver]. This was offset by [top negative driver].'

Return all 5 explanations with plots and text summaries.

When to use this prompt

Use case 01

You need easy-to-read explanations for specific individual cases.

Use case 02

The audience cares about examples more than global theory.

Use case 03

You want to compare high, low, borderline, and failure cases.

Use case 04

You need short human-readable summaries to accompany plots.

What the AI should return

Five LIME-based local explanations with contribution plots and short plain-English summaries explaining what pushed each prediction up or down.

How to use this prompt

1

Open your data context

Load your dataset, notebook, or working environment so the AI can operate on the actual project context.

2

Copy the prompt text

Use the copy button above and paste the prompt into the AI assistant or prompt input area.

3

Review the output critically

Check whether the result matches your data, assumptions, and desired format before moving on.

4

Chain into the next prompt

Once you have the first result, continue deeper with related prompts in Explainability.

Frequently asked questions

What does the LIME Explanation prompt do?+

It gives you a structured explainability starting point for data scientist work and helps you move faster without starting from a blank page.

Who is this prompt for?+

It is designed for data scientist workflows and marked as intermediate, so it works well as a guided starting point for that level of experience.

What type of prompt is this?+

LIME Explanation is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.

Can I use this outside MLJAR Studio?+

Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.

What should I open next?+

Natural next steps from here are Counterfactual Explanations, Decision Tree Proxy, Feature Importance.