While working with R, you might face the Error in eval(family$initialize) : y values must be 0 <= y <= 1. If you don’t know what to do in this case, this guide can help you out. Keep reading to learn why this error occurs and how to fix it.

What Causes Error in eval(family$initialize) : y values must be 0 <= y <= 1?

Data Or Dependent Variable Is Not A Factor

You will encounter the eval(family$initialize) problem if your dependent variable or data is not a factor. The reason behind this is that categorical data are represented by factors that are a component of R’s data structure. They are crucial for statistical analysis and might be ordered or unordered.

Run A Logistic Model On Numerical Data

The eval(family$initialize) error is unavoidable when running a logistic model on numerical data. This is because the logistic model should be used when the dependent variable is binary. These binary variables are Yes or No, True or False, and 0 or 1.

Therefore, using anything different to run a logistic model will lead to the error in eval(family$initialize).

Run Probit Model On Non-Binary Data

The Probit model can work on the binary data, such as 0 and 1. Still, running the Probit model on data sets with mixed data results in the error in eval(family$initialize).

How To Fix Error in eval(family$initialize) : y values must be 0 <= y <= 1

Convert Type “Direction” To “Factor”

The error demands y integers between 1 and 0 since your data’s categorical features, like direction are of character type.

You must convert these features to factor type using as.factor(data$Direction).

Output:

glm(Direction ~ lag2, data=...)

Notice that stock.direction does not need to be declared.

You can also check the variable class by utilizing the class(variable) command. In case the variables are character, you may convert them to factor and add a different column in that same DataFrame.

Utilize stringAsFactors=T

Error in eval(family$initialize) : y values must be 0 <= y <= 1 can be solved by adding stringAsFactors=T to the function red.csv.

Here is an example.

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

Output:

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

The Bottom Line

Now you know how to deal with the Error in eval(family$initialize) : y values must be 0 <= y <= 1. If you ever encounter this error again, you will know what to do and quickly solve the problem.Suppose you need to help with other errors in the R programming language; check out our guide on fixing error: vector memory exhausted (limit reached) or geom_path: each group consists of only one observation. Your problem will soon be solved, and you can continue working on your R project.