In this study we introduce an ensemble of neural networks, in which each member is a linear perceptron. Our main objective is to build an ensemble of neural networks that can automatically and effectively divide the problem space and assign a subspace to each member. By assigning only a portion of the problem space, we expect that the learning difficulty for each member can be reduced, thus leading to better classification ability. To investigate the effectiveness of the proposed method in dividing the problem space, in this paper we deal with ensemble consists only of linear perceptrons, each with an additional output neuron that indicates the confidence level of the output.