Learn Before
Parameters to specify when training a k-Nearest Neighbors algorithm
- A distance metric
- K = the of the nearest neighbors to use in making a prediction
- Optional weighting function on the neighbor points
- Method for aggregating the classes of neighbor points
0
1
Tags
Data Science
Related
Reference for KNN
Parameters to specify when training a k-Nearest Neighbors algorithm
Which of the following is true about the k-nearest neighbors classification algorithm, assuming uniform weighting on the k neighbors? Select all that apply.
What class would a KNeighborsClassifer classify the new point as for k = 1 and k = 3?
Which of the following is true for the nearest neighbor classifier?
Learn After
Specifying a distance metric for k-Nearest Neighbors algorithm
Specifying K = the number of the nearest neighbors for a k-Nearest Neighbors algorithm
Specifying the optional weighting function on the neighbor points for a k-Nearest Neighbors algorithm
Specifying a method for aggregating the classes of neighbor points for a k-Nearest Neighbors algorithm