Conditional Dependencies

Conditional dependencies refer to the relationships between variables in a dataset that are dependent on the values of other variables. In other words, the relationship between two variables is not fixed, but rather depends on the value of a third variable. This concept is important in data science because it allows us to model complex relationships between variables and make more accurate predictions. For example, in a medical dataset, the relationship between a patient's age and their risk of developing a certain disease may depend on their gender or family history. By modeling these conditional dependencies, we can better understand the factors that contribute to the disease and develop more effective treatments.

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Matching Condition: Matching condition refers to the process of comparing two or more datasets or variables to identify similarities or differences between them. In data science, matching condition is often used in data preprocessing and cleaning to ensure tha ... Read More >>
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Conditional Dependencies

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