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Business Intelligence
Notes Misuse of Data/Inaccurate Data
Data assembled through data mining using ethical purposes can be misused. This information
may be exploited by unethical people or companies to take advantage in various ways which
not only limits to fake identity proof creation and pass confidential data to competitors. Also if
incorrect data is used for decision-making, it will affect the results of the company.
11.7 Data Mining Models
There are several different types of data mining models:
1. Predictive models: These types of models predict how likely an event is to occur. Usually,
higher the score, the more likely the event is to occur.
Example: How likely an online transaction is to be fraudulent, or how likely a railway
passenger is to be a thief, or how likely a company is to go bankrupt.
2. Summary models: These models are used to summarize data.
Example: It can be used to divide online transactions or railway passengers into different
groups depending upon their characteristics.
3. Network models: This type of model represents data by nodes and links.
Example: In a network model describing Facebook friends, nodes might be individuals
and directed edges with weights might represent the likelihood that one friend will contact
another friend in the next 24 hours.
4. Association models: Association models are used to find and characterize co-occurrences.
Example: Purchases of certain items, such as soft drink and pizza together will be
represented by association models.
Self Assessment
Fill in the blanks:
12. ............................ type of model represents data by nodes and links.
13. ...................................... are used to find and characterize co-occurrences.
11.8 Data Mining Algorithms
A data mining algorithm is a set of heuristics and calculations that creates a data mining model
from data. The algorithm first analyses the data you provide, looking for specific types of
patterns or trends and then creates the data.
Analysis Services includes the following algorithm types:
Classification algorithms: This type of algorithm predicts one or more discrete variables,
based on the other attributes in the dataset.
Regression algorithms: This type of algorithm predicts one or more continuous variables,
such as profit or loss, based on other attributes in the dataset.
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