Association rules use the

O apriori

O associati

O incarini

O logetti

algorithm to find frequentlv associated attributes in a data set

Association rules data mining is often used to produce

O forecasts

O recommendations

O ideations

O predictions

The mathematical formula for calculating the

divided hv the number of times it could have occurred in the data set.

O support

O confidence

O Laplace

O gain

ercent is the number or times an associaton did occur

The mathematical formula for calculating the

percent is the number of times an association aid occur

divided by the number of times the premise (or antecedent) occurred in the data set.

O support

O confidence

O Laplace

O gain

True or false: A support percent of 18% in an association set would be considered too low to be of any use

True

False

True or false: A confidence percent of 18% in an association set would be considered too low to be of an use

True

False

The onerator reau1red in Randiner to fina treauencv natterns in a data set is called

O FP-Detect

O FP-Growth

O FP-Associate

O Fp-Find

True or false: FP-Growth creates association rules in RapidMiner.

True

False

True or false: In RapidMiner, if the min support parameter on the FP-Growth operator is set at 0.8 and the min

confidence on the Create Association Rules overator is set at .75. the software mav still return rules if an association true or false