Font size
WorksheetsIntro to Data Mining
Total questions: 16
Worksheet time: 6mins
Data Mining is also referred to as
Exploratory Data Analysis
Knowledge discovery from Databases
None of the above
Classification is
A subdivision of a set of examples into a number of classes
A measure of the accuracy, of the classification of a concept that is given by a certain theory
The task of assigning a classification to a set of examples
None of these
Data selection is
The actual discovery phase of a knowledge discovery process
The stage of selecting the right data for a KDD process
A subject-oriented integrated time variant non-volatile collection of data in support of management
None of these
What should be written in the blue box?
Transformed data
Pattern/model
Preprocessed data
Raw data
Using features to predict unknown or future values of the same or other feature is known as ___________ power of data mining
Clustering
Predictive
Associative
Descriptive
Fraud-detection models and risk mitigation models-these are examples of data mining solution for which discipline?
Health
Insurance
Banking
Retail
Class label is unknown: Group data to form new classes, e.g., cluster houses to find distribution patterns
Predictive Analysis
Anomaly Detection
Association Mining
Cluster analysis
Choose which data mining task is the most suitable for the following scenario: Identifying an unexpected/unusual amount of spending
Prediction
Sequential pattern analysis
Association rules
Anomaly detection
Choose which data mining task is the most suitable for the following scenario: detecting the dosage of medicine for a certain treatment
Prediction
Classification
Association rules
Sequential pattern analysis
Choose which data mining task is the most suitable for the following scenario: determining the thumbs up/thumbs down of a social media post
Prediction
Association rules
Classification
Clustering
Choose which data mining task is the most suitable for the following scenario:
To identify items that are bought concomitantly by a reasonable fraction of customers so that they can be shelved.
Classification
Association rules
Clustering
Prediction
Choose which data mining task is the most suitable for the following scenario:
Predict fraudulent cases in credit card transactions
Classification
Association rules
Anomaly detection
Clustering
Choose which data mining task is the most suitable for the following scenario:
Given is a set of objects, with each object associated with its own time of events, find rules that predict strong sequential dependencies among different events
Classification
Sequential pattern analysis
Clustering
Association rules
What is the use of data cleaning?
to remove the noisy data
correct the inconsistencies in data
transformations to correct the wrong data.
All of the above
__________ may be defined as the data objects that do not comply with the general behavior or model of the data available.
Outlier Analysis
Evolution Analysis
Prediction
Classification
This is an example of ________________
Data inconsistency
Data redundancy
Data security
Data consistency
