scikit-learn 1.4.1 Other versions
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00:27.093 total execution time for auto_examples_gaussian_process files:
Gaussian process classification (GPC) on iris dataset (plot_gpc_iris.py)
plot_gpc_iris.py
00:11.869
0.0 MB
Comparison of kernel ridge and Gaussian process regression (plot_compare_gpr_krr.py)
plot_compare_gpr_krr.py
00:05.241
Ability of Gaussian process regression (GPR) to estimate data noise-level (plot_gpr_noisy.py)
plot_gpr_noisy.py
00:03.408
Probabilistic predictions with Gaussian process classification (GPC) (plot_gpc.py)
plot_gpc.py
00:03.043
Illustration of prior and posterior Gaussian process for different kernels (plot_gpr_prior_posterior.py)
plot_gpr_prior_posterior.py
00:01.409
Illustration of Gaussian process classification (GPC) on the XOR dataset (plot_gpc_xor.py)
plot_gpc_xor.py
00:01.154
Gaussian Processes regression: basic introductory example (plot_gpr_noisy_targets.py)
plot_gpr_noisy_targets.py
00:00.555
Gaussian processes on discrete data structures (plot_gpr_on_structured_data.py)
plot_gpr_on_structured_data.py
00:00.255
Iso-probability lines for Gaussian Processes classification (GPC) (plot_gpc_isoprobability.py)
plot_gpc_isoprobability.py
00:00.157
Forecasting of CO2 level on Mona Loa dataset using Gaussian process regression (GPR) (plot_gpr_co2.py)
plot_gpr_co2.py
00:00.002