0
我有一個非常大的數據集，其中包含6個輸出列的36個功能。我試圖在這個數據集中進行MLP反向傳播神經網絡學習（迴歸），我正在使用神經網絡和插入符號。我想要兩層隱藏層，每層有6個和5個節點。我也想k重交叉驗證添加到我的神經網絡模型神經網絡，插入符號和交叉驗證
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()
其中的X和Y的特徵和分別預測數據幀
但它給錯誤和警告
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.
您對列車命令的使用是錯誤的。如果在此處指定了調整參數，則會出現錯誤。在這種情況下，隱藏的層。 – phiver
我用適當的圖層參數編輯了代碼，但仍然給出錯誤 – Eka
實際數據是什麼樣的？你只有1個預測變量，還是x有多列的矩陣？你的Y是一個因素嗎？ – Alos