perceptron

  感知器感知器算法训练二元线性分类器。结构体数据使用感知器学习规则 找到给定的二分类标签数据超平面。 (PERCEPTRON Perceptron algorithm to train binary linear classifier. Synopsis: model = perceptron(data) model = perceptron(data,options) model = perceptron(data,options,init_model) Description: model = perceptron(data) uses the Perceptron learning rule to find separating hyperplane from given binary labeled data. model = perceptron(data,options) specifies stopping condition of the algorithm in structure options: .tmax [1x1]... maximal number of iterations. If tmax==-1 then it only returns index (model.last_update) of data vector which should be used by the algorithm for updating the linear rule in the next iteration. model = perceptron(data,options,init_model) specifies initial model which must contain: .W [dim x 1] ... normal vector. .b [1x1] ... bias of hyperplane. .t [1x1] (optional) ... iteration number. Input: data [struct] Labeled (binary) training data. .X [dim x num)