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v0.5.0

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@fabsig fabsig released this 15 Mar 16:03
· 1111 commits to master since this release
v0.5.0
d024bd9
  • add function in R and Python packages that allows for choosing tuning parameters using deterministic or random grid search
  • faster training and prediction for grouped random effects models for non-Gaussian data when there is only one grouping variable
  • faster training and prediction for Gaussian process models for non-Gaussian data when there are duplicate locations
  • faster prediction for grouped random effects models for Gaussian data when there is only one grouping variable
  • support pandas DataFrame and Series in Python package
  • fix bug in initialization of score for the GPBoost algorithm for non-Gaussian data
  • add lightweight option for saving booster models with gp_models by not saving the raw data (this is the new default)
  • update eigen to newest version (commit b271110788827f77192d38acac536eb6fb617a0d)
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