Question: True or False? A random - forest classification model creates many different decision trees for a data set and then, based on each tree's prediction,

True or False? A random-forest classification model creates many different decision trees for a data
set and then, based on each tree's prediction, the trees essentially vote to select the tree that produces
the best result.
True or False? The support vector machine (SVM), often called SVC (support vector classifier),
classifies data by separating values with a box called a hypersquare.
True or False? In data classification, the dependent variable is the class to which the algorithm will
assign the data.
True or False? In classification, the accuracy score is the sum of the correct category assignments.
Neural networks are at the heart of machine learning and are used for a wide range of applications,
including classification.
True or False? Python is one of the world's most popular programming languages and is used to
create solutions that range from websites, data mining, machine learning, visualization, and more.
True or False? Python is an interpreted language, as opposed to a compiled language, for which the
Python interpreter executes one statement at a time.
True or False? Unlike other programming languages that use braces {} to group related statements,
Python instead relies on statement indentation to group statements.
True or False? Data cleansing is normally a one-time event.
True or False? The goal of the data-governance board is to continually improve the quality of data.
True or False? Database developers refer to the process of correcting such data inconsistences as
"normalizing the data."
True or False? The data-quality assessment framework provides eight standard measurements based
on quality dimensions.
True or False? Developers often refer to the process of transforming and cleansing data as "data
wrangling," or, depending upon with whom you are speaking, "data munging."
 True or False? A random-forest classification model creates many different decision

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