假设神经网络的训练样本有𝑚个,每个包含一组输入𝑥和一组输出信号𝑦,𝐿表示神经网 络层数,𝑆𝐼表示每层的neuron 个数(𝑆𝑙表示输出层神经元个数),𝑆𝐿代表最后一层中处理单元 的个数。 将神经网络的分类定义为两种情况:二类分类和多类分类, 二类分类:𝑆𝐿 = 0, 𝑦 = 0 𝑜𝑟 1表...
A protein backbone structure is designable if a substantial number of amino acid sequences exist that autonomously fold into it1,2. It has been suggested that the designability of backbones is governed mainly by side chain-independent or side chain type-insensitive molecular interactions3,4,5, in...
You're definitely not trying for the impossible. Neural networks areuniversal approximators- meaning that for any function F and error E, there existssomeneural network (needing only a single hidden layer) that can approximate F with error less than E. ...
Searching for possible biochemical networks that perform a certain function is a challenge in systems biology. For simple functions and small networks, this can be achieved through an exhaustive search of the network topology space. However, it is diffic
This result tells us that neural networks have a kind ofuniversality. No matter what function we want to compute, we know that there is a neural network which can do the job. What's more, this universality theorem holds even if we restrict our networks to have just a single layer interme...
Function fitting is the process of training a neural network on a set of inputs in order to produce an associated set of target outputs. After you construct the network with the desired hidden layers and the training algorithm, you must train it using a set of training data. Once the neur...
The activation ops provide different types of nonlinearities for use in neural networks. These include smooth nonlinearities (sigmoid,tanh, andsoftplus), continuous but not everywhere differentiable functions (relu,relu6, andrelu_x), and random regularization (dropout). ...
https://hit-scir.gitbooks.io/neural-networks-and-deep-learning-zh_cn/content/chap3/c3s3.html Coursera, Andrew Ng 公开课第一周,第三周,第五周 http://math.stackexchange.com/questions/477207/derivative-of-cost-function-for-logistic-regression ...
In addition, we mainly discussed a novel machine learning method, radial basis function neural networks (RBFNN) to construct QSPR/QSAR models and made some evaluation on the established models. 基于径向基函数神经网络(RBFNN)方法所建立的这个最优的QSPR模型给出的结果如下:对于训练集的平方相关系数(R...
所谓激活函数(Activation Function),就是在人工神经网络的神经元上运行的函数,负责将神经元的输入映射到输出端。咦?百度百科给出的解释好像不是很好理解呀。 In artificial neural networks, the activation function of a node defines the output of that node given an input or set of inputs. A standard inte...