ML-Apriori Algorithm

What is the primary objective of the Apriori Algorithm?

• To build a decision tree

• To discover frequent itemsets in transactional databases

• To classify data into classes

• To perform clustering analysis

Which type of learning does the Apriori Algorithm belong to?

• Supervised learning

• Unsupervised learning

• Semi-supervised learning

• Reinforcement learning

What is a frequent itemset in the context of the Apriori Algorithm?

• An itemset that occurs only once in the dataset

• An itemset with items in alphabetical order

• An itemset that occurs frequently in the dataset above a specified threshold

• An itemset with the most items in the dataset

Which data structure is commonly used to store the candidate itemsets in the Apriori Algorithm?

• Linked list

• Stack

• Array

• Hash table

What is the minimum threshold used to identify frequent itemsets in the Apriori Algorithm?

• 0

• 1

• 0.5

• It can vary depending on the dataset and the problem.

The Apriori Algorithm uses which principle to reduce the search space?

• Minimum Description Length

• Occam's Razor

• Support and Confidence

• Downward Closure Property

Which step is performed in the pruning phase of the Apriori Algorithm?

• Generating candidate itemsets

• Calculating support and confidence

• Eliminating itemsets that violate the downward closure property

• Building the decision tree

What is the drawback of the Apriori Algorithm when dealing with large datasets?

• It requires labeled data for training.

• It cannot handle categorical attributes.

• It may generate an exponential number of candidate itemsets.

• It is sensitive to outliers.

Which association rule metric is used to measure how often a rule is correct?

• Lift

• Confidence

• Support

• Conviction

The Apriori Algorithm is most commonly used for which type of data analysis?

• Regression analysis

• Classification analysis

• Clustering analysis

• Association rule mining