What do you mean by Dummy Variable? Where it is used in Machine Learning?

If there are n number of categories in categorical attribute, n new attributes will be created. These attributes created are called Dummy Variables. These dummy variables will be created with one hot encoding and each attribute will have value either 0 or 1, representing presence or absence of that attribute.

We use dummy variables in Regression in Machine Learning. For transforming categorical attribute to numerical attribute, we can use label encoding procedure (label encoding assigns a unique integer to each category of data). But this procedure is not alone that much suitable, hence, one hot encoding is used in regression models following label encoding. This enables us to create new attributes according to the number of classes present in the categorical attribute. Here is where dummy variables are used.