ITM 4273 ch.5 T/F
Associations are a type of pattern that discovers time-ordered events, such as predicting that an existing banking customer who already has a checking account will open a savings account followed by an investment account within a year.
false
Mass, length, time, plane angle, energy, and electric charge are examples of physical measures whose data are represented in interval scales.
false
at the highest level of abstraction, all data can be divided into interval data and ratio data
false
data mining requires a separate, dedicated database
false
in order to be applied successfully, a data mining study must be viewed as a set of automated software tools and techniques
false
the first step in the data mining process is to understand the relevant data from the available databases
false
two types of categorical data are nominal and ordinal data
true
steps to CRISP-DM process
1. business understanding 2. data understanding 3. data presentation 4. model building 5. testing and evaluation 6. deployment
data preprocessing steps
1. consolidation 2. cleaning 3. transformation 4. reduction
data mining offers organizations a decision-enhancing environment to exploit opportunities by transforming data into a strategic weapon
true
the data mining environment is usually a client-server architecture or a Web-based information systems architecture
true
Clustering partitions a collection of things, such as objects and events presented in a structured dataset into segments whose members share similar characteristics
true
Compared to the other steps in CRISP-DM, data preprocessing consumes the most time and effort; most believe that this step accounts for roughly 80 percent of the total time spent on a data mining project
true
Cross-Industry Standard Process for Data Mining, or CRISP-DM, is one of the most popular nonproprietary standard methodologies for data mining
true
Data mining is a way for companies to develop business intelligence from their data to gain a better understanding of their customers and operations and to solve complex organizational problems
true
Data types such as date/time, unstructured text, image, and audio need to be converted into some form of categorical or numeric representation before they can be processed by data mining algorithms.
true
Newer Web-based tools enable managers at all educational levels to do data mining
true
Predictions tell the nature of future occurrences of certain events based on what has happened in the past, such as predicting the winner of the Super Bowl or forecasting the absolute temperature of a particular day.
true
Technically speaking, data mining is a process that uses statistical, mathematical, and artificial intelligence techniques to extract and identify useful information and subsequent knowledge from large sets of data.
true
The variable marital status can be categorized using the codes (1) single, (2) married, and (3) divorced. These codes are examples of ordinal data.
true
a common example of interval scale movement is temperature on the Celsius scale
true
data mining is a prime candidate for better management of companies that are data-rich but knowledge-poor
true