Association Rule Mining Quiz

Froggy Jumps

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Basics of mining rules across datasets

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Malaviga Masilamani

India

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Association Rule Mining Quiz


Froggy Jumps Association Rule Mining QuizOnline version Basics of mining rules across datasets by Malaviga Masilamani 1 What is the focus of Single Dimensional Boolean Association Rules? a Rules using numeric item quantities in transactions b Rules derived from multi-table relational joins c Rules based on presence/absence of a single item in transactions 2 From which data source are Transaction Databases primarily used for mining? a Static CSV files with no timestamps b Single-row relational tables c Dynamically stored item transactions with timestamps 3 What distinguishes Multilevel Association Rules? a Rules that operate at different item hierarchies or levels b Rules that ignore hierarchies c Rules limited to a single level of items 4 What does Dimensional Association Rules extend to? a Rules that ignore facts and dimensions b Only single-dimension data c Multiple dimensions in the data warehouse (facts, dimensions) 5 Which data environment enables Multidimensional Association Rules? a Relational databases and Data Warehouses with star/snowflake schemas b NoSQL documents only c Flat files with no schema 6 What is a key characteristic of Multidimensional Association Rules? a Rules restricted to binary items b Rules that do not consider time c Rules across multiple dimensions (e.g., product, store, time) 7 Which concept is central to mining from Transaction Databases? a Clustering based on distance metrics b Neural network weights c Frequent itemsets and association rules like A -> B 8 In data warehouses, which structure often supports Multidimensional Rules? a Cube structures (OLAP cubes) with measures and dimensions b Unstructured text stores c Flat tables only 9 What does Boolean in this context imply? a Items are always in a single state b Items are either present (true) or absent (false) in a transaction c Items have continuous quantity values 10 Which stage is typical before deriving association rules? a Frequent itemset mining (e.g., Apriori, FP-Growth) b Supervised label selection c Time-series forecasting 11 What is the primary goal of decision tree induction in classification? a To encode all numeric features as branches only b To build a tree that partitions data to predict the target class c To maximize the number of leaves regardless of accuracy 12 Which method uses Bayes' theorem for classification? a K-means clustering b Bayesian classification c Support vector regression 13 In backpropagation, which elements are adjusted to reduce prediction error? a Weights of the connections b Activation functions only c Feature scaling parameters 14 Association rule mining can help derive what type of rules for classification? a Linear regression rules b Classification rules c Decision rules only for clustering 15 A common metric to evaluate classifier performance is? a Accuracy b Mean squared error c F1-score only for imbalanced data 16 What issue can distort accuracy when classes are imbalanced? a Overfitting due to too many trees b Underfitting due to excessive pruning c Class imbalance leading to biased accuracy 17 Which split criterion is often used to grow decision trees? a Random split b Entropy c Information gain 18 Which learning paradigm uses labeled examples to learn mappings? a Unsupervised learning b Supervised learning c Reinforcement learning 19 In association rule mining, which metric measures how often a rule is trusted? a Confidence b Lift c Support 20 What is a purpose of pruning in decision trees? a To increase tree depth b To maximize the number of rules c To avoid overfitting and simplify the tree

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Association Rule Mining Quiz

Froggy Jumps

About this activity

Created by

Download the paper version to play

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Association Rule Mining QuizOnline version

by Malaviga Masilamani

What is the focus of Single Dimensional Boolean Association Rules?

From which data source are Transaction Databases primarily used for mining?

What distinguishes Multilevel Association Rules?

What does Dimensional Association Rules extend to?

Which data environment enables Multidimensional Association Rules?

What is a key characteristic of Multidimensional Association Rules?

Which concept is central to mining from Transaction Databases?

In data warehouses, which structure often supports Multidimensional Rules?

What does Boolean in this context imply?

Which stage is typical before deriving association rules?

What is the primary goal of decision tree induction in classification?

Which method uses Bayes' theorem for classification?

In backpropagation, which elements are adjusted to reduce prediction error?

Association rule mining can help derive what type of rules for classification?

A common metric to evaluate classifier performance is?

What issue can distort accuracy when classes are imbalanced?

Which split criterion is often used to grow decision trees?

Which learning paradigm uses labeled examples to learn mappings?

In association rule mining, which metric measures how often a rule is trusted?

What is a purpose of pruning in decision trees?