Maternal Health Risk Factors for Predictive Modeling in Remote Areas

A classification dataset curated for evaluating machine learning models on independent and identically distributed tabular data. It originates from a 2020 study on maternal health risk factors in remote areas using IoT. The dataset is licensed under CC BY 4.0.

Use Cases

• Benchmarking classification models for IID tabular data based on the dataset's stated focus.
• Analyzing risk factors for maternal health based on the original study's description.
• Evaluating model performance on data with a high rate of duplicate entries as noted in curation comments.

Strengths

• Licensed under the permissive CC BY 4.0 license.
• Curated specifically for evaluating predictive ML models on IID tabular data.

Limitations

• The dataset contains a high anomaly of 55% duplicate rows.
• Row count, column names, sample data, and file formats are unknown.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

Original data sourced from https://doi.org/10.24432/C5DP5D, referenced in a 2020 Springer conference proceeding.

Collection Method

Curated by the TabArena team from the original source for a tabular ML study.

Time Range

Dataset year is 2020.

Freshness

Dataset year is 2020; last update date is unknown.

Geography

Likely focuses on remote areas, potentially Kuantan, Pahang, Malaysia, as referenced in the source paper.