Conclusion. Encoding categorical data is a crucial step in data preprocessing. By converting categorical data into a numeric format, machine learning models can interpret and work more effectively.

Ordinal data. This type of categorical data consists of a set of orders or scales. For example, a list of patients consists of the level of sugar present in the body of a person which can be divided ...

Data encoding and transformation are the processes of converting data from one format or structure to another, such as changing the data type, encoding scheme, scale, or units. These processes are ...

This command will connect to big_database_full_of_legacy_tables and change all the tables to utfmb4 encoding and utf8mb4_unicode_ci collation; it will use the pt-online-schema-change tool, if ...

When encoding binary and categorical data, there are four cases you must deal with: independent (x) binary data, dependent (y) binary data, independent (x) categorical data and dependent (y) ...

This study addresses a tampered-data recovery problem for linear discrete-time systems with completely unknown system dynamics under stealthy attacks. The basic idea is to identify the stealthy attack ...