![]() Binary or Dichotomous is essentially the variables that can have only two outcomes such as Win/Lose, On/Off, and so on.The categorical variables can be further subdivided into the following categories : In this article, we are going to deal with the various methods to convert Categorical Variables into Dummy Variables which is an essential part of data pre-processing, which in itself is an integral part of the Machine Learning or Statistical Model. All of these variables can be classified into two types of data: Quantitative and Categorical. These data sets are composed of Independent Variables or the features and the Dependent Variables or the Labels. A grouped or composite entity holding the relevant to a particular problem together is called a data set. ML | Label Encoding of datasets in PythonĪll the statistical and machine learning models are built on the foundation of data.ML | One Hot Encoding to treat Categorical data parameters.Introduction to Hill Climbing | Artificial Intelligence.Best Python libraries for Machine Learning.Activation functions in Neural Networks.Elbow Method for optimal value of k in KMeans. ![]()
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