Can someone please show me how to resolve this error?

```
#load libraries
library(dplyr)
library(GA)
# create some data for this example
a1 = rnorm(1000,100,10)
b1 = rnorm(1000,100,5)
c1 = sample.int(1000, 1000, replace = TRUE)
train_data = data.frame(a1,b1,c1)
fitness <- function(x) {
#bin data according to random criteria
train_data <- train_data %>%
mutate(cat = ifelse(a1 <= x[1] & b1 <= x[3], "a",
ifelse(a1 <= x[2] & b1 <= x[4], "b", "c")))
train_data$cat = as.factor(train_data$cat)
#new splits
a_table = train_data %>%
filter(cat == "a") %>%
select(a1, b1, c1, cat)
b_table = train_data %>%
filter(cat == "b") %>%
select(a1, b1, c1, cat)
c_table = train_data %>%
filter(cat == "c") %>%
select(a1, b1, c1, cat)
#calculate quantile ("quant") for each bin
table_a = data.frame(a_table%>% group_by(cat) %>%
mutate(quant = ifelse(c1 > x[5],1,0 )))
table_b = data.frame(b_table%>% group_by(cat) %>%
mutate(quant = ifelse(c1 > x[6],1,0 )))
table_c = data.frame(c_table%>% group_by(cat) %>%
mutate(quant = ifelse(c1 > x[7],1,0 )))
#group all tables
final_table = rbind(table_a, table_b, table_c)
# calculate the total mean : this is what needs to be optimized
mean = mean(final_table$quant)
}
lbound <- c(80,80,80,80,0,0,0)
ubound <- c(120,120,120,120,1,1,1)
#error:
curve(fitness, from = lbound, to = ubound, n = 1000)
points(GA@solution, GA@fitnessValue, col = 2, pch = 19)
```

Thanks