Here is my code:

train_points <- read.table("kaggle_train_points.txt", sep="\t") train_labels <- read.table("kaggle_train_labels.txt", sep="\t") test_points <- read.table("kaggle_test_points.txt", sep="\t") #uses package 'class' library(class) knn(train_points, test_points, train_labels, k = 5); 

dim(train_points) is 42000 x 784
dim(train_labels) is 42000 x 1

I don't see the issue, but I'm getting the error :

Error in knn(train_points, test_points, train_labels, k = 5) :
'train' and 'class' have different lengths.

What's the problem?

8 Answers

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) 

I had the same issue in trying to apply knn on breast cancer diagnosis from wisconsin dataset I found that the issue was linked to the fact that cl argument need to be a vector factor (my mistake was to write cl=labels , I thought this was the vector to be predicted it was in fact a data frame of one column ) so the solution was to use the following syntax : knn (train, test,cl=labels$diagnosis,k=21) diagnosis was the header of the one column data frame labels and it worked well Hope this help !

I have recently encountered a very similar issue. I wanted to give only a single column as a predictor. In such cases, selecting a column, you have to remember about drop argument and set it to FALSE. The knn() function accepts only matrices or data frames as train and test arguments. Not vectors.

knn(train = trainSet[, 2, drop = FALSE], test = testSet[, 2, drop = FALSE], cl = trainSet$Direction, k = 5)

Try converting the data into a dataframe using as.dataframe(). I was having the same problem & afterwards it worked fine:

train_pointsdf <- as.data.frame(train_points) train_labelsdf <- as.data.frame(train_labels) test_pointsdf <- as.data.frame(test_points) 

Simply set drop = TRUE while you're excluding cl from dataframe, it causes to remove dimension from an array which have only one level:

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

I had a similar error when I was reading to a tibble (read_csv) and when I switched to read.csv the code worked.

Followed the code as given in the book but will show error due to mismatch lengths (1 is df other is vector returned). I reached here but nothing worked exactly but ideas helped that vectors were needed for comparison.

This throws error

gmodels::CrossTable(x = wbcd_test_labels, # actuals y = wbcd_test_pred, # predicted prop.chisq = FALSE) 

The following works :

gmodels::CrossTable(x = wbcd_test_labels$diagnosis, # actuals y = wbcd_test_pred, # predicted prop.chisq = FALSE) 

where using $ for x makes it a vector and hence matches

Additionally while running knn

Cl parameter shoud also have vector save labels in vectors else there will be length mismatch OR use labelDF$Class_label

wbcd_test_pred <- knn(train = wbcd_train, test = wbcd_test, cl =wbcd_train_labels$diagnosis, #note this k = 21) 

Hope this helps beginners like me.

Uninstall R Previous versions and install R version > 4.0. It will work.