Boolean flags

The Boolean flags labeling technique involves the use of binary indicators to assign labels to data instances. These indicators, often represented as Boolean variables (true/false or 1/0), are associated with specific characteristics or properties that help identify the desired label. By examining the presence or absence of these flags, data instances can be automatically labeled.

The Boolean flags labeling technique finds applications across various domains in machine learning. Some common applications include the following:

• Data filtering: Boolean flags can be used to filter and label data instances based on specific criteria. For example, in sentiment analysis, a positive sentiment flag can be assigned to text instances that contain positive language or keywords, while a negative sentiment flag can be assigned to instances with negative language.
• Event detection: Boolean flags can aid in labeling instances to detect specific events or conditions. For...