Deck 4: Data Mining Process, Methods, and Algorithms

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Question
In the Miami-Dade Police Department case, the department chose to start small and grow big in order to demonstrate success with data mining.
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The entire focus of the predictive analytics system in the Visa case was on detecting and handling fraudulent charges for the company's benefit.
Question
Decision trees are most appropriate for categorical data and interval data.
Question
In the terrorist funding case study, predictive analytics helped to identify abnormal transfer prices on exports.
Question
Using data mining on data about imports and exports can help to detect tax avoidance and money laundering.
Question
In the cancer research case study, data mining algorithms that predict cancer survivability with high predictive power are good replacements for medical professionals.
Question
Market basket analysis is a useful and entertaining way to explain data mining to a technologically less savvy audience, but it has little business significance.
Question
Which index has been used in economics to measure the diversity of a population?

A) Atkinson
B) Lorenz
C) Stockholm
D) Gini
Question
________ data have finite nonordered values (e.g., gender data, which have two values: male and female).
Question
________ is the splitting mechanism used in ID3, which is perhaps the most widely known decision tree algorithm.
Question
List five reasons for the growing popularity of data mining in the business world.
Question
Describe the difference between quantitative and qualitative data. Include definitions for nominal and ordinal data.
Question
List and briefly describe the six steps of the CRISP-DM data mining process.
Question
Briefly describe five techniques (or algorithms) that are used for classification modeling.
Question
In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing?
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Deck 4: Data Mining Process, Methods, and Algorithms
1
In the Miami-Dade Police Department case, the department chose to start small and grow big in order to demonstrate success with data mining.
True
2
The entire focus of the predictive analytics system in the Visa case was on detecting and handling fraudulent charges for the company's benefit.
False
3
Decision trees are most appropriate for categorical data and interval data.
True
4
In the terrorist funding case study, predictive analytics helped to identify abnormal transfer prices on exports.
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5
Using data mining on data about imports and exports can help to detect tax avoidance and money laundering.
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6
In the cancer research case study, data mining algorithms that predict cancer survivability with high predictive power are good replacements for medical professionals.
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7
Market basket analysis is a useful and entertaining way to explain data mining to a technologically less savvy audience, but it has little business significance.
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8
Which index has been used in economics to measure the diversity of a population?

A) Atkinson
B) Lorenz
C) Stockholm
D) Gini
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Unlock for access to all 15 flashcards in this deck.
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k this deck
9
________ data have finite nonordered values (e.g., gender data, which have two values: male and female).
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10
________ is the splitting mechanism used in ID3, which is perhaps the most widely known decision tree algorithm.
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11
List five reasons for the growing popularity of data mining in the business world.
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12
Describe the difference between quantitative and qualitative data. Include definitions for nominal and ordinal data.
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13
List and briefly describe the six steps of the CRISP-DM data mining process.
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14
Briefly describe five techniques (or algorithms) that are used for classification modeling.
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15
In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing?
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