📊Analyse de donnéesIntermediateAll AIs

Analyze feature importance

Understand model feature importance

Paste in your AI

Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.

Write Python code to compute and visualize feature importance from a trained [Random Forest/XGBoost/LightGBM] model. Include: built-in importance, permutation importance (on test set), and SHAP values. Compare methods and identify discrepancies. Highlight the top 15 features with a plot.

Personalize this prompt with Léa

Answer 3 questions and Léa tailors the prompt to your situation.

Use Cases

Understand model feature importance

Improve this prompt

Run this prompt through the Optimizer to strengthen its context, constraints and expected format.

Improve this prompt with the Optimizer

Comments

Be the first to comment on this prompt.

Glossary Terms

Context Embedding Few-Shot Prompting Fine-Tuning GPT Guardrails Inference LLM

📬 Get new prompts every week

Join our newsletter and never miss a prompt.

Go further

Improve this prompt with the Optimizer

Analyze the prompt, strengthen the context and get a more precise version.

Prompt Engineering

Cross-model principles for writing more reliable prompts.

Similar Prompts

📊Analyse de donnéesAdvancedAll AIs

Build a recommendation system

Build recommendation systems

0108

📊Analyse de donnéesBeginnerAll AIs

Create an automated EDA report

Generate EDA reports automatically

0101

📊Analyse de donnéesIntermediateAll AIs

Build a feature engineering pipeline

Create reproducible preprocessing pipelines

0104

📊Analyse de donnéesIntermediateAll AIs

Handle imbalanced classes

Fix class imbalance

099