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sklears-gaussian-process-0.2.0
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sklears-gaussian-process 0.2.0
Gaussian Process models for regression and classification
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automatic_kernel.rs
batch_bayesian_optimization.rs
bayesian_optimization.rs
classification.rs
constrained_bayesian_optimization.rs
convolution_processes.rs
deep_gp.rs
features.rs
fitc.rs
gpc.rs
gpr.rs
heteroscedastic.rs
hierarchical.rs
intrinsic_coregionalization.rs
kernel_optimization.rs
kernel_selection.rs
kernel_structure_learning.rs
kernel_trait.rs
kernels.rs
lib.rs
lib_old.rs
lib_refactored_with_errors.rs
linear_model_coregionalization.rs
marginal_likelihood.rs
multi_objective.rs
multi_output.rs
multi_task.rs
noise_function_learning.rs
nystrom.rs
random_fourier_features.rs
regression.rs
robust.rs
sparse_gpr.rs
sparse_spectrum.rs
spatial.rs
structured_kernel_interpolation.rs
temporal.rs
utils.rs
variational.rs
variational_deep_gp.rs
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//!
Multi-output Gaussian Process models
use
scirs2_core
::
ndarray
::
array
;