What does KNN stand for in machine learning?

kNN + Naive Bay

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Linh Khánh
Used 2+ times
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10 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
K-Nearest Neighbors
Known Nearest Nodes
Knowledge Network Navigator
Kernel Nearest Network
2.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
In KNN, what does the 'K' represent?
The number of clusters
The distance metric
The number of nearest neighbors to consider when making a prediction
The number of features in the dataset
3.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
What kind of distance metrics are commonly used in KNN to find the nearest neighbors?
Euclidean distance, Manhattan distance, or Minkowski distance
Correlation distance, Angular distance, or Time-series distance
Mahalanobis distance, Dice distance, or Edit distance
Logistic distance, Fisher distance, or Dynamic distance
4.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
Is KNN more suitable for classification, regression, or both?
Classification only
Regression only
Both, but it is most commonly used for classification
Neither classification nor regression
5.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
What is a potential drawback of KNN regarding large datasets?
KNN becomes more accurate with large datasets
KNN loses its memory with large datasets
KNN is unable to handle large datasets due to overfitting
KNN can be computationally expensive and slow for large datasets
6.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
What is the key assumption made by Naive Bayes about features?
All features are dependent on each other
It assumes all features are independent of each other
It assumes all features have the same distribution
It assumes features are randomly distributed
7.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
Is Naive Bayes a probabilistic or deterministic algorithm?
Probabilistic algorithm
Deterministic algorithm
Cluster-based algorithm
Distance-based algorithm
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