BCOR 2205 Quiz 3 exam with correct |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
answers
Machine Learning - correct answer✔✔The practice of using algorithms to parse data, learn
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from it, and then make a determination or prediction about something in the word
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Algorithm - correct answer✔✔a process or set of rules to be followed in calculations or other
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problem-solving operations, especially by a computer. |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
Training Set - correct answer✔✔subsection of a dataset from which the machine learning
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
algorithm uncovers or "learns" relationships between the features and the target variable
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(64%)
Validation (test) Set - correct answer✔✔subsection of a dataset to which we apply the
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machine learning algorithm to see how accurately it identifies relationships between the
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known outcomes for the target variable and the dataset's other features (16%)
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Holdout Set - correct answer✔✔a subsection of a dataset to provide a final estimate of the
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machine learning model's performance after if has been trained and validated. Holdout sets
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should never be used to make decisions about which algorithms to use for improving tuning
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
algorithms. (20 % of data set) |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
Over Training (Over Fitting) - correct answer✔✔Poor generalization
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Boolean variable - correct answer✔✔references one of two values, True or False, Yes or No, 1
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or 0 (binary)
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target - correct answer✔✔the variable we are trying to predict and gain insights about
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answers
Machine Learning - correct answer✔✔The practice of using algorithms to parse data, learn
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
from it, and then make a determination or prediction about something in the word
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
Algorithm - correct answer✔✔a process or set of rules to be followed in calculations or other
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
problem-solving operations, especially by a computer. |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
Training Set - correct answer✔✔subsection of a dataset from which the machine learning
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
algorithm uncovers or "learns" relationships between the features and the target variable
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
(64%)
Validation (test) Set - correct answer✔✔subsection of a dataset to which we apply the
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
machine learning algorithm to see how accurately it identifies relationships between the
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
known outcomes for the target variable and the dataset's other features (16%)
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
Holdout Set - correct answer✔✔a subsection of a dataset to provide a final estimate of the
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
machine learning model's performance after if has been trained and validated. Holdout sets
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
should never be used to make decisions about which algorithms to use for improving tuning
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
algorithms. (20 % of data set) |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
Over Training (Over Fitting) - correct answer✔✔Poor generalization
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
Boolean variable - correct answer✔✔references one of two values, True or False, Yes or No, 1
|||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\ |||\\\
or 0 (binary)
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target - correct answer✔✔the variable we are trying to predict and gain insights about
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