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How do you deal with high cardinality features?

How do you deal with high cardinality features?

Dealing with categorical features with high cardinality: Target Encoding

  1. Label Encoding (scikit-learn): i.e. mapping integers to classes.
  2. One Hot / Dummy Encoding (scikit-learn): i.e. expanding the categorical feature into lots of dummy columns taking values in {0,1}.

What is cardinality of a categorical feature?

In the context of machine learning, “cardinality” refers to the number of possible values that a feature can assume. For example, the variable “US State” is one that has 50 possible values.

What is impact coding?

Impact coding is a bridge from Naive Bayes (where each variable’s impact is added without regard to the known effects of any other variable) to Logistic Regression (where dependencies between variables and levels is completely accounted).

What is cardinality in data science?

In the world of databases, cardinality refers to the number of unique values contained in a particular column, or field, of a database. If you have multiple indexed columns, each with a large number of unique values, then the cardinality of that cross product can get really large.

What is cardinality of a table?

The cardinality of a relation is the number of tuples it contains. Cardinality refers to the uniqueness of data values contained in a particular column (attribute) of a database table. The lower the cardinality, the more duplicated elements in a column.

What is the degree and cardinality of a table?

Answer: Degree is the number of attributes or columns present in a table. Cardinality is the number of tuples or rows present in a table.

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What is minimum and maximum cardinality?

Minimum cardinality is the minimum number of instances of an entity that can be associated with each instance of another entity. Maximum cardinality is the maximum number of instances of an entity that can be associated with each instance of another entity.

What is mandatory and optional relationships?

In a mandatory relationship, every instance of one entity must participate in a relationship with another entity. In an optional relationship, any instance of one entity might participate in a relationship with another entity, but this is not compulsory. Important.

Can you have a many to many relationship?

A many-to-many relationship occurs when multiple records in a table are associated with multiple records in another table. To avoid this problem, you can break the many-to-many relationship into two one-to-many relationships by using a third table, called a join table. …

What is an attribute in ER diagram?

Attributes are included to include details of the various entities that are highlighted in a conceptual ER diagram. Attributes are characteristics of an entity, a many-to-many relationship, or a one-to-one relationship. Multivalued attributes are those that are can take on more than one value.

What is a relationship called when an association is maintained between three entities?

A relationship degree indicates the number of entities or participants associated with a relationship. A unary relationship exists when an association is maintained within a single entity. A ternary relationship exists when three entities are associated.

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How do you identify relationships between entities?

  1. Identify Entities. The entities in this system are Department, Employee, Supervisor and Project.
  2. Find Relationships. We construct the following Entity Relationship Matrix:
  3. Draw Rough ERD.
  4. Fill in Cardinality.
  5. Define Primary Keys.
  6. Draw Key-Based ERD.
  7. Identify Attributes.
  8. Map Attributes.

What do double diamonds represent in an ER diagram?

Explanation: Diamonds represent relationship sets in an ER diagram. Relationship sets define how two entity sets are related in a database. Explanation: The double diamonds represent the relationship sets linked to weak entity sets. Weak entity sets are the sets that do not have a primary key.