Census Data
Identify relevant attributes:
- Capital gain/loss are not relevant because many attributes are zero
- Age (we expect it to be linear but the majority of >50k is in the range of 40 years)
- Work class is unbalanced (the majority of people works in private), coverage is very low
- Education number
- Marital status (interesting, married is different)
- Occupation (interesting)
Education and education-num are perfectly correlated (it is duplicated).
We can enhance accuracy by replacing missing values:
Preprocess - filter - unsupervised - attribute - replacemissingvalues
Apriori Algorithm
We apply discretization and perform a manual analysis of the data in order to identify any correlation between pairs of attributes.
Last update:
November 8, 2022 10:52:23
Created: October 18, 2022 10:04:20
Created: October 18, 2022 10:04:20
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