
Classification
Authored by Amer Mahyoub
Computers
University
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12 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
The ratio of correctly predicted positive observations is known as:
Precision
Accuracy
Bias
Recall
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of a confusion matrix?
Helps to select the best model
Calculate precision and accuracy
Table that describes the performance of a classification model
To generate a classification report
3.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
Which elements will you see in a classification report?
mean squared error
recall
R2 value
accuracy
4.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
Which models use weak learners?
Random Forests
Decision Tree
XGBoost
Support Vector Machines
5.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
Which functions might we use for preprocessing categorical data?
get_dummies()
to_string()
StandardScaler()
LabelEncoder()
6.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
What can you learn from the decision tree visualization?
How many nodes and branches the model has.
How accurate the model is.
Whether the model might be overfitting.
How deep the tree goes.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How is recall defined?
The total percent of accurate predictions
The proportion of predicted positives that are accurate
The proportion of actual positives that are accurate
The proportion of true positives to true negatives
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