Genome Sequence Classification Model Comparison with Random Forest and CNN

This dataset compares the random forest and 1-D CNN models for classifying genome sequences. The dataset is 5.5 KB in size and was authored by Sathish Sankar. It is licensed under CC BY 4.0 and was last updated in March 2026.

Use Cases

• Compare Random Forest Classification and 1-D CNN model performance on genome sequences using reported metrics like F1 scores.
• Analyze genomic differences and variant surveillance based on features like Escape Mutations or 2 Delta Variant.
• Study genomic changes following evolution using features such as Four Vanished Mutations.
• Apply machine learning models for viral evolutionary studies and supporting preparedness based on genomic features.

Strengths

• Dataset is openly licensed under CC BY 4.0.
• Includes tags indicating specific genomic features like Escape Mutations and 2 Delta Variant for analysis.
• Last updated in March 2026, indicating recent maintenance.

Limitations

• Very small dataset at 5.5 KB, limiting the scope and scale of analysis.
• Unknown row and column structure, hindering direct application of standard ML workflows.
• Content appears focused on a specific model comparison study, not raw genomic sequence data.

Provenance

Source

figshare, author Sathish Sankar.

Collection Method

null

Time Range

null

Freshness

Last updated 2026-03-19.

Geography

null