【发布时间】：2023-04-04 07:44:02
【问题描述】：
我有一个非常大的数据集，其中包含 36 个特征，其中包括 6 个输出列。我正在尝试在该数据集中执行 MLP 反向传播神经网络学习（回归），并且我正在使用神经网络和插入符号。我想要两个隐藏层，每层有 6 个和 5 个节点。我还想在我的 NN 模型中添加 k 折交叉验证
control <- trainControl(method="repeatedcv", number=5, repeats=1)
# train the model
model <- train(X,Y, method="neuralnet",
algorithm = "backprop", learningrate = 0.25,act.fct = 'tanh',
tuneGrid = data.frame(layer1 = 2:6, layer2 = 2:6, layer3 = 0),threshold = 0.1, trControl=control)
warnings()
其中 X 和 Y 分别是特征和预测数据帧
但它给出错误和警告
Error in train.default(X, Y, method = "neuralnet", algorithm = "backprop", :
wrong model type for classification
> warnings()
Warning messages:
1: In eval(expr, envir, enclos) :
model fit failed for Resample01: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
2: In eval(expr, envir, enclos) :
model fit failed for Resample02: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
3: In eval(expr, envir, enclos) :
model fit failed for Resample03: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
4: In eval(expr, envir, enclos) :
model fit failed for Resample04: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
5: In eval(expr, envir, enclos) :
model fit failed for Resample05: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
6: In eval(expr, envir, enclos) :
model fit failed for Resample06: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
7: In eval(expr, envir, enclos) :
model fit failed for Resample07: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
8: In eval(expr, envir, enclos) :
model fit failed for Resample08: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
9: In eval(expr, envir, enclos) :
model fit failed for Resample09: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
10: In eval(expr, envir, enclos) :
model fit failed for Resample10: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
11: In eval(expr, envir, enclos) :
model fit failed for Resample11: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
12: In eval(expr, envir, enclos) :
model fit failed for Resample12: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
13: In eval(expr, envir, enclos) :
model fit failed for Resample13: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
14: In eval(expr, envir, enclos) :
model fit failed for Resample14: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
15: In eval(expr, envir, enclos) :
model fit failed for Resample15: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
16: In eval(expr, envir, enclos) :
model fit failed for Resample16: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
17: In eval(expr, envir, enclos) :
model fit failed for Resample17: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
18: In eval(expr, envir, enclos) :
model fit failed for Resample18: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
19: In eval(expr, envir, enclos) :
model fit failed for Resample19: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
20: In eval(expr, envir, enclos) :
model fit failed for Resample20: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
21: In eval(expr, envir, enclos) :
model fit failed for Resample21: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
22: In eval(expr, envir, enclos) :
model fit failed for Resample22: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
23: In eval(expr, envir, enclos) :
model fit failed for Resample23: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
24: In eval(expr, envir, enclos) :
model fit failed for Resample24: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
25: In eval(expr, envir, enclos) :
model fit failed for Resample25: layer1=4, layer2=1, layer3=1 Error in if (reached.threshold < min.reached.threshold) { :
missing value where TRUE/FALSE needed
26: In nominalTrainWorkflow(x = x, y = y, wts = weights, info = trainInfo, ... :
There were missing values in resampled performance measures.
【问题讨论】：
-
您对 train 命令的使用是错误的。如果在此处指定调整参数，则会出现错误。在这种情况下是隐藏层。
-
我已经用适当的图层参数编辑了代码，但仍然给出错误
-
您的实际数据是什么样的？您只有 1 个预测变量还是 x 是具有多列的矩阵？你的 Y 是一个因素吗？
标签： r neural-network r-caret