Hyperparameter Search Spaces for Machine and Deep Learning Models

A collection of hyperparameter search spaces for machine learning and deep learning models, authored by Shuo Xu and last updated on 2026-05-29. The dataset is published on figshare under a CC-BY-4.0 license and is stored in an XLS file format. Its small size of 9.5 KB suggests a focused collection of configuration parameters.

Use Cases

• Benchmarking hyperparameter optimization algorithms based on provided search spaces.
• Configuring automated machine learning (AutoML) pipelines with standardized parameter ranges.
• Comparing model performance across different hyperparameter configurations.
• Teaching concepts of hyperparameter tuning in machine learning courses.

Strengths

• Explicitly licensed as CC-BY-4.0, allowing for broad reuse.
• Small file size (9.5 KB) enables quick download and inspection.
• Last update timestamp (2026-05-29) is provided for recency assessment.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Freshness

Last updated 2026-05-29 17:34:08; freshness should be verified.