Dichotomy
Jump to navigation
Jump to search
A Dichotomy is a classification task that divides an entire set into two subsets
- See: Binary Attribute, Conceptual Model, Partition of a Set, Jointly Exhaustive, Mutually Exclusive, Complement (Set Theory), Logic, Dual (Category Theory), Proposition, Continuous Variable, Categorical Variable, Binary Variable, Discretization.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Dichotomy Retrieved:2017-6-18.
- A dichotomy is a partition of a whole (or a set) into two parts (subsets). In other words, this couple of parts must be
- jointly exhaustive: everything must belong to one part or the other, and
- mutually exclusive: nothing can belong simultaneously to both parts.
- Such a partition is also frequently called a bipartition.
The two parts thus formed are complements. In logic, the partitions are opposites if there exists a proposition such that it holds over one and not the other.
Treating continuous variables or multicategorical variables as binary variables is called dichotomization. The discretization error inherent in dichotomization is temporarily ignored for modeling purposes.
- A dichotomy is a partition of a whole (or a set) into two parts (subsets). In other words, this couple of parts must be
2000
- (Witten & Frank, 2000) ⇒ Ian H. Witten, and Eibe Frank. (2000). “Data Mining: Practical Machine Learning Tools and Techniques with Java implementations." Morgan Kaufmann.