Planning: Patient State Binary Classification Dataset

The Planning dataset originates from the UCI ML repository. It is a binary classification dataset where the target task is to determine if a patient is in a planning state. The dataset was uploaded to Hugging Face by the user 'mstz' on October 8, 2025.

Use Cases

• Train a binary classifier to predict patient planning state based on clinical features.
• Benchmark classification algorithms on a clinical decision support task.
• Analyze feature importance for determining a patient's planning status.

Strengths

• Dataset is sourced from the established UCI Machine Learning Repository.
• Task is clearly defined as binary classification for a clinical state.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

UCI Machine Learning Repository.

Freshness

Last updated 2025-10-08 09:42:17; freshness should be verified.