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 784dim(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.
