Help with the confusionMatrix for accuracy on the validation/training sets in R!

Here is my dataset code:

# Read in the heart statlog file and recode:

heart <- read.table("https://archive.ics.uci.edu/ml/machine-learning-databases/statlog/heart/heart.dat", header = FALSE)

names(heart) <- c("age", "sex", "cpt", "rbp", "serum", "fbs", "rer", "mhr", "eia",

"oldpeak", "slope", "nmaj", "thal", "class")

recoded_heart <- heart %>%

mutate(sex = recode_factor(sex, "0" = "female", "1" = "male"),

cpt = recode_factor(cpt, "1" = "typical angina", "2" = "atypical angina",

"3" = "non anginal pain", "4" = "asymptomatic"),

fbs = recode_factor(fbs, "1" = "true", "0" = "false"),

rer = recode_factor(rer, "0" = "normal", "1" = "wave abnormal", "2" = "left hypertrophy"),

eia = recode_factor(eia, "0" = "no", "1" = "yes"),

slope = recode_factor(slope, "1" = "up", "2" = "flat", "3" = "down"),

thal = recode_factor(thal, "3" = "normal", "6" = "fixed defect", "7" = "reversable defect"),

class = recode_factor(class, "1" = "absence", "2" = "presence"))

recoded_heart$class = as.factor(recoded_heart$class)

Here is the code with creating the training/test and validation sets:

# Creating the training and validation set:

set.seed(1)

library(caTools)

split = sample.split(recoded_heart$class, SplitRatio = 0.8)

heart_train = subset(recoded_heart, split == TRUE)

heart_test = subset(recoded_heart, split == FALSE)

# Checking number of rows and column in each set

print(dim(heart_train))

print(dim(heart_test))

# Building the model

model_glm = glm(class~ . , family = "binomial",

data = heart_train, maxit = 100)

# Predictions on the validation set

predictTest = predict(model_glm, newdata = heart_test,

type = "response")

predicted.class <- transmute(data.frame(predictTest), class = ifelse

(predictTest > 0.5, "presence", "absence"))

# Confusion Matrix tells the accuracy and precision of the validation set:

print(confusionMatrix(predicted.class$class, recoded_heart$class))

# Confusion Matrix tells the accuracy and precision of the training set:

print(confusionMatrix(heart_train$class, recoded_heart$class))

I get an error about the arguments needing to have the same length. Please help!