
Classification and Clustering
Authored by Andy Ohemeng
Computers
University
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8 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is a classification algorithm?
K-means
DBSCAN
Decision Tree
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which metric is commonly used to evaluate the performance of a classification model?
Accuracy
Sum of Squared Errors
Mean Absolute Error
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of the confusion matrix in classification?
To visualize the data distribution
To evaluate the clustering quality
To summarize the prediction results
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which algorithm is best suited for a binary classification problem?
K-mean
Logistic Regression
KNN
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is a non-hierarchical clustering algorithm?
K-means
Dendogram
Ward’s Method
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the goal of clustering in data analysis?
To predict a target variable
To group similar items together
To reduce the number of features
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary difference between agglomerative and divisive hierarchical clustering?
There is no difference; they are the same
Agglomerative starts with all points as clusters and merges them, while divisive starts with one cluster and splits it
Agglomerative is used for large datasets, while divisive is for small datasets
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