Description: LabelEncoder is a class in Scikit-learn that converts categorical labels into numerical format. This process is fundamental in machine learning, as many algorithms require input data to be numeric for calculations to be performed. LabelEncoder assigns a unique integer to each category in a dataset, allowing categorical variables to be correctly interpreted by machine learning models. This class is particularly useful in situations where working with categorical data that has no inherent order, such as city names, product types, or text categories. By transforming these labels into numbers, data manipulation and analysis are facilitated, enabling models to learn patterns and relationships more effectively. Additionally, LabelEncoder is part of the Scikit-learn library, which is widely used in the data science and machine learning community, ensuring its relevance and applicability in various projects and studies.
