In this paper, we present the results of an experimental comparison among seven different weight initialization methods in twelve different problems. The comparison is performed by measuring the speed of convergence, the generalization capability and the probability of successful convergence. It is not usual to find an evaluation of the three properties in the papers on weight initialization. The training algorithm was Backpropagation (BP) with a hyperbolic tangent transfer function. We found that the performance can be improved with respect to the usual initialization scheme.