Timber Building Seismic Response Data for MLR Analysis

4000 timber building samples detail structural parameters and seismic response metrics. Dongqi Wei published this dataset in 2026, derived from the public Timber Seismic Performance Dataset on Kaggle. It supports analysis of inter-story drift and roof displacement under seismic loading.

Use Cases

• Predict roof displacement levels (low, medium, high) from structural parameters using Gradient Boosted Random Forest models.
• Analyze the influence of key structural and seismic elements on roof displacement via Multiple Linear Regression (MLR).
• Optimize seismic performance characteristics like inter-story drift to guide structural design decisions.
• Visualize high-dimensional feature relationships for structural parameter patterns using t-SNE embeddings.
• Tune hyperparameters for seismic response prediction models using the Scalable Cheetah Optimizer (SCO).

Strengths

• Contains 4000 samples of timber building data.
• Data pre-processing employed Robust Scaling and Isolation Forest for outlier detection.
• Associated model achieved a prediction accuracy of 0.949 for roof displacement classification.

Limitations

• Dataset size is 5.5 KB, indicating a very limited number of features or columns.
• Specific column names and data types are not provided, complicating direct analysis.
• The temporal and geographic coverage of the original source data is unknown.

Provenance

Source

Derived from the Timber Seismic Performance Dataset, a publicly available Kaggle repository.

Collection Method

Samples obtained from the source repository, with pre-processing involving normalization and outlier detection.

Freshness

Last updated in April 2026.