> #trainControl这个函数是为了设置train函数重采样的方式,例如这里就是使用五折交叉验证的方法 > trControl <- trainControl(method = 'cv',number = 5,selectionFunction = 'oneSE') > #expand.grid是用来设置需要调整的参数及调整的范围,结果用在train函数中 > grid <- expand.grid(.model='tree', + .tri...
该 trainControl 函数有一个参数 summaryFunction ,用于指定计算性能的函数。该函数应具有以下参数: data是一个数据框或矩阵的参考,其列名为obs和pred,用于观察和预测结果值(用于回归的数字数据或用于分类的字符值)。目前,类的概率没有被传递给函数。data中的值是对单一调谐参数组合的保留预测值(及其相关参考值)。如...
The mid-morning train from Colombo, in Tea Country. See Sri Lanka by train Sri Lanka is a fabulous place, safe, friendly and remarkably hassle-free. Sri Lanka's railways are a great way to get around and a real cultural experience. The train rides will be highlights of your trip, such...
createDataPartition()对数据进行训练集和测试集的简单无放回分割；bootstrap samples()进行有放回的分组...
学的断断续续。近期需要完成一些数据建模与分析，将机器学习重新整理了一遍。这篇文章主要是介绍R数据...
# During model building, Keras calls this function with # target_class_ids of type float32. Unclear why. Cast it # to int to get around it. target_class_ids=tf.cast(target_class_ids,'int64') # Find predictions of classes that are not in the dataset. ...
collapse all in page Syntax trainedNet = train(net,X,T,Xi,Ai,EW) [trainedNet,tr] = train(net,X,T,Xi,Ai,EW) [trainedNet,tr] = train(net,X,T,Xi,Ai,EW,Name,Value) Description This function trains a shallow neural network. For training deep learning networks (such as convolutional ...
There was no security chain on the compartment door, but the main lock did function (after a bit of fiddling around). We could lock it ourselves from inside when leaving, and then just needed to ask the attendant to open it with the staff key when we returned. The window and screen ...
The function arguments are defined in the Python raster function class. This is where you list additional deep learning parameters and arguments for experiments and refinement, such as a confidence threshold for adjusting sensitivity. The names of the arguments are populated from reading the Python mo...
Specify a reset function, defined at the end of the example, that sets random initial conditions. Get agentBlk = mdl + "/RL Agent"; env = rlSimulinkEnv(mdl,agentBlk,obsInfo,actInfo); env.ResetFcn = @localResetFcn; Create TD3 Agent The agent used in this example is a twin-delaye...