skopt.benchmarks.hart6¶

skopt.benchmarks.hart6(x, alpha=array([1. , 1.2, 3. , 3.2]), P=array([[0.1312, 0.1696, 0.5569, 0.0124, 0.8283, 0.5886], [0.2329, 0.4135, 0.8307, 0.3736, 0.1004, 0.9991], [0.2348, 0.1451, 0.3522, 0.2883, 0.3047, 0.665 ], [0.4047, 0.8828, 0.8732, 0.5743, 0.1091, 0.0381]]), A=array([[10. , 3. , 17. , 3.5 , 1.7 , 8. ], [ 0.05, 10. , 17. , 0.1 , 8. , 14. ], [ 3. , 3.5 , 1.7 , 10. , 17. , 8. ], [17. , 8. , 0.05, 10. , 0.1 , 14. ]]))[source][source]¶

The six dimensional Hartmann function is defined on the unit hypercube.

It has six local minima and one global minimum f(x*) = -3.32237 at x* = (0.20169, 0.15001, 0.476874, 0.275332, 0.311652, 0.6573).

More details: <http://www.sfu.ca/~ssurjano/hart6.html>

Examples using skopt.benchmarks.hart6¶

Comparing initial point generation methods¶

Visualizing optimization results¶