Logistic Regression on factor: Error in eval(family$initialize) : y values must be 0 <= y <= 1

Question

Not able to fix the below error for the below logistic regression

training=(IBM$Serial<625)
data=IBM[!training,]

stock.direction <- data$Direction
training_model=glm(stock.direction~data$lag2,data=data,family=binomial)

###Error### ---- Error in eval(family$initialize) : y values must be 0 <= y <= 1

Few rows from the data i am using

X   Date    Open    High    Low Close   Adj.Close   Volume  Return  lag1    lag2    lag3    Direction   Serial
1   28-11-2012  190.979996  192.039993  189.270004  191.979996  165.107727  3603600 0.004010855 0.004010855 -0.001198021    -0.006354834    Up  1
2   29-11-2012  192.75  192.899994  190.199997  191.529999  164.720734  4077900 0.00114865  0.00114865  -0.004020279    -0.009502386    Up  2
3   30-11-2012  191.75  192 189.5   190.070007  163.465073  4936400 0.003630178 0.003630178 -0.001894039    -0.005576956    Up  3
4   03-12-2012  190.759995  191.300003  188.360001  189.479996  162.957703  3349600 0.001213907 0.001213907 -0.002480478    -0.001636046    Up  4

You have `Direction` variable as character (up). it will not work — Mateusz1981, Nov 29 '17 at 06:55
isnt logistic regression suppose to work on qualitative variables ?? Any fix u would suggest — Akhil Doppalapudi, Nov 29 '17 at 07:00
but you need to change variable to 1 or 0 as the error measage says you so if ýou have to categories ex up and down you can use `ifelse` to change them to 0 and 1s — Mateusz1981, Nov 29 '17 at 07:04

score 17 · Answer 1 · edited May 01 '18 at 01:02

17

The reason it's asking for y values between 0 and 1 is because the categorical features in your data such as 'direction' are of type 'character'. You need to convert them to type 'factor' with as.factor(data$Direction). So: glm(Direction ~ lag2, data=...) Don't need to declare stock.direction.

You can check the class of variables by using the command class(variable), and if they're character, you can convert to factor and create a new column in the same data frame. It should work then.

edited May 01 '18 at 01:02

smci

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answered Jan 27 '18 at 16:29

Nidhi Agarwal

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1

Just reference `as.factor(data$Direction)`. So: `glm(Direction ~ lag2, data=...)` Don't need to declare stock.direction. – smci Apr 30 '18 at 22:06

score 4 · Answer 2 · edited Aug 15 '22 at 09:54

4

I was getting the same error

Error in eval(family$initialize) : y values must be 0 <= y <= 1" and solved it by adding "stringsAsFactors=T

to the read.csv function.

BEFORE : gene.train = read.csv("gene.train.csv", header=T) # error

AFTER : gene.train = read.csv("gene.train.csv", header=T, stringsAsFactors=T) # no error.

edited Aug 15 '22 at 09:54

user438383

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answered Oct 07 '20 at 18:29

binmosa

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score 0 · Answer 3 · answered Nov 29 '17 at 09:11

Without understanding the data, you should do st like this

library(dplyr)
df <- read.table(header = T, stringsAsFactors = F,  text ="X   Date    Open    High    Low Close   Adj.Close   Volume  Return  lag1    lag2    lag3    Direction   Serial
1   28-11-2012  190.979996  192.039993  189.270004  191.979996  165.107727  3603600 0.004010855 0.004010855 -0.001198021    -0.006354834    Up  1
2   29-11-2012  192.75  192.899994  190.199997  191.529999  164.720734  4077900 0.00114865  0.00114865  -0.004020279    -0.009502386    Up  2
3   30-11-2012  191.75  192 189.5   190.070007  163.465073  4936400 0.003630178 0.003630178 -0.001894039    -0.005576956    Up  3
4   03-12-2012  190.759995  191.300003  188.360001  189.479996  162.957703  3349600 0.001213907 0.001213907 -0.002480478    -0.001636046    Up  4
1   28-11-2012  190.979996  192.039993  189.270004  191.979996  165.107727  3603600 0.004010855 0.004010855 -0.001198021    -0.006354834    Up  1
2   29-11-2012  192.75  192.899994  190.199997  191.529999  164.720734  4077900 0.00114865  0.00114865  -0.004020279    -0.009502386    Down  2
3   30-11-2012  191.75  192 189.5   190.070007  163.465073  4936400 0.003630178 0.003630178 -0.001894039    -0.005576956    Up  3
4   03-12-2012  190.759995  191.300003  188.360001  189.479996  162.957703  3349600 0.001213907 0.001213907 -0.002480478    -0.001636046    Down  4
") %>%
  mutate(bin = ifelse(Direction == "Up", 1, 0))

glm(bin ~ High, family = "binomial", data = df)

Logistic Regression on factor: Error in eval(family$initialize) : y values must be 0 <= y <= 1

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