Airline Customer Satisfaction Survey Data for Predictive Modeling

A Kaggle dataset from 2023, curated by the TabArena team for their Tabular ML IID Study. It is intended for evaluating classification models on independent and identically distributed tabular data. The original data source is a customer satisfaction survey for an airline.

Use Cases

• Predict customer satisfaction status based on survey feedback features.
• Benchmark classification algorithms on a curated IID tabular dataset.
• Analyze factors influencing airline service quality from customer feedback data.

Strengths

• Dataset is explicitly curated for evaluating predictive ML models on IID tabular data.
• License is CC0: Public Domain, allowing for unrestricted use.

Limitations

• Row count, column count, and file size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle User Yakhyojon, 'Customer Satisfaction in Airline' (2023).

Collection Method

Curated from Kaggle by the TabArena team; original collection method unknown.

Time Range

Dataset year is 2023.

Freshness

Dataset year is 2023, but last updated date is unknown.

Geography

Geography is not specified in the provided metadata.