Mindmap
DR by BINNING

Inhalt der Mindmap
DR by BINNING
WHAT?
- A data discretisation method
- Aimed at reducing the number of values assumed by an attribute.
- HOW TO REDUCE?
- By transforming continuous attributes into categorical attributes characterized by a limited number of distinct values.
- EG
- the weekly spending of a mobile phone customer is a continuous attribute.
- With binning, the continuous value of weekly spending can be binned into five categories as follows:
- In this case, the binning process reduces the number of distinct values for the attribute of weekly spending of a mobile phone customer.
- With binning, the continuous value of weekly spending can be binned into five categories as follows:
- the weekly spending of a mobile phone customer is a continuous attribute.
- EG
- By transforming continuous attributes into categorical attributes characterized by a limited number of distinct values.
- HOW TO REDUCE?
- Aimed at reducing the number of values assumed by an attribute.
- A data discretisation method
EG OF BINNING METHODS
- • Subjective subdivision
- Classes are defined based on the experience and judgment of domain experts.
- • Automated subdivision
- Subdivision into categories may be automatically determined based on equal size or equal width
- • Subjective subdivision
IBM SPSS Modeler
- Binning node allows the automatic conversions of numerical fields into categorical fields.
- EG
- an income field can be transformed into a new categorical field containing income groups of equal width
- EG
- Binning node allows the automatic conversions of numerical fields into categorical fields.
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- Beschreibung
- Data Mining Mindmap am DR by BINNING, erstellt von sue san am 11/02/2017.
- Erstellt von
- sue san
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