caret包是一个用于构建、训练和评估机器学习模型的R包,提供了丰富的功能来帮助用户进行模型训练和参数调优。train函数是caret包的核心功能之一,用于训练模型,支持多种算法和模型类型。我们先用train函数拟合神经网络模型。 set.seed(1234) nn.model <- train( 结局~ 指标1+指标2+指标3+指标4+指标5+指标6,...
我们这里使用软件包neuralnet,配套有绘图等函数,另外还有caret用于机器学习非常方便的软件包,软件安装并加载,如下: if (!require(neuralnet)) install.packages("neuralnet") if (!require(vcd)) install.packages("vcd") if (!require(caret)) install.packages("caret") library(caret) library(neuralnet) library...
1. 软件安装 我们这里使用软件包neuralnet,配套有绘图等函数,另外还有caret用于机器学习非常方便的软件包,软件安装并加载,如下: if (!require(neuralnet)) install.packages("neuralnet") if (!require(vcd)) install.packages("vcd") if (!require(caret)) install.packages("caret") library(caret) library(neur...
Five-fold cross-validation were performed by the Caret package, pROC package was used to estimate the value of AUC30. Additional data verification. On three independent datasets (GSE47460, GSE53845 and GSE110147), the validity of the constructed classification scoring model of IPF disease ...
R Added R/caret.r. It's more convenient for testing various optimizatio… Jun 6, 2017 extras predict function in src/piconn.cpp modified to handle arbitrary D sizes. May 1, 2017 src Removed obsolete variable N from src/piconn.cpp. May 5, 2017 ...
Additional algorithms were trained using the caret package (6.0.78) in R. Data were split into 80% training set and 20% test set. The following algorithms were included: logistic regression with elastic net penalty (glmnet package, version 2.0.13); SVMs with linear, polynomial, or radial bas...
In this case, special algorithms are used. D: level of input data and their manipulations At this level, the source data is fed to the input of the neural network for training. How to manipulate the input data to provide a high diversity and high individual accuracy? Bootstrap samples ...
The way of information processing is greatly affected by absence or presence of feedback loops in the network. If there are no feedback loops between neurons (i.e. the network has a structure of sequential layers where every neuron receives information only from the previous layer), information...
This article is a continuation of previous articles on deep neural network and predictor selection. Here we will cover features of a neural network initiated by Stacked RBM, and its implementation in the "darch" package.
removing predictors that have only one unique value in any class (method = “conditionalX”). All these operations are implemented in the preProcess()::caret function by means of the methods considered above. These operations are carried out for the complete data set before the division into th...