Replication Data for: A machine learning-based Bayesian optimization solution to nonlinear responses in dusty plasmas
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Python code for machine learning method to extract coefficients for equation of motion of two interacting dust particles in a plasma environment.  Data from experimental measurement of the thermal motion of two vertically-aligned particles are given in the Matlab workspace' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bayesian optimization","dusty plasma","ion wake","machine learning"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Python code for machine learning method to extract coefficients for equation of motion of two interacting dust particles in a plasma environment.  Data from experimental measurement of the thermal motion of two vertically-aligned particles are given in the Matlab workspace' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Python code for machine learning method to extract coefficients for equation of motion of two interacting dust particles in a plasma environment.  Data from experimental measurement of the thermal motion of two vertically-aligned particles are given in the Matlab workspace
Bayesian optimization; dusty plasma; ion wake; machine learning