Knn in R: 'Train and Class Have Different Lengths'

KNN in R: 'train and class have different lengths'?

Without access to the data, it's really hard to help. However, I suspect that train_labels should be a vector. So try

cl = train_labels[,1]
knn(train_points, test_points, cl, k = 5)

Also double check:

dim(train_points)
dim(test_points)
length(cl)

knn train and class have different lengths

The knn function in R requires the training data to only contain independent variables, as the dependent variable is called separately in the "cl" parameter. Changing the line below will fix this particular error.

pred_knn <- knn(train=df[,c(1,2)], test=df_new, cl=df$golf, k=1)

However, note that running the above line will throw another error. Since knn calculates the Euclidean distance between observations, it requires all independent variables to be numeric. These pages have helpful related information. I would recommend using a different classifier for this particular data set.

https://towardsdatascience.com/k-nearest-neighbors-algorithm-with-examples-in-r-simply-explained-knn-1f2c88da405c
https://discuss.analyticsvidhya.com/t/how-to-resolve-error-na-nan-inf-in-foreign-function-call-arg-6-in-knn/7280/4

Hope this helps.

train' and 'class' have different lengths error in R

Your cl variable is not the same length as your train variable. MLValidY only has 74 observations, while TrainXNormDF has 224.

cl should provide the true classification for every row in your training set.

Furthermore, cl is a data.frame instead of a vector.

Try the following:

NN <- knn(train = TrainXNormDF, 
      test = ValidXNormDF,
      cl = MLTrainY$`MLTrain[, 9]`,
      k = 3)

Why do we get error saying train and class have different lengths while using Knn function in R?

The class parameter should be provided as a vector, not as a dataframe. Referring to Diagnosis variable in your wbcd_train_labels dataframe should work

wbcd_test_pred <- knn(train = wbcd_train, test = wbcd_test,
cl = wbcd_train_labels$Diagnosis,...)

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