Tabular

Feature Importance

Analyze and rank feature importance in tabular data

490K runs

Note: This playground provides simulated output to showcase functionality. No input data is processed or stored on our servers. Use this demo to explore the feature extractor's capabilities before integrating it into your application.

Input

Text Input string

Enter the text you want to process

# method string

Method to use for importance calculation. Default: random_forest

# target_column string

Required

Target column for importance analysis. Default: undefined

Output

{
  "importance_scores": [
    {
      "feature": "education",
      "importance": 0.35,
      "rank": 1
    },
    {
      "feature": "experience",
      "importance": 0.28,
      "rank": 2
    }
  ],
  "method": "random_forest",
  "target_column": "salary",
  "model_performance": {
    "r2_score": 0.82,
    "mse": 0.15
  }
}

Ready to run Feature Importance on your data? Spin it up in Studio — no infra to host.

Run this in Studio

Already have embeddings? Skip extraction — search your own vectors with MVS. First 1M vectors free.

Try MVS →