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GO Classes DPP | ML |K-NN

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We have a dataset of $1000$ points for a classification problem using the $k$-NN algorithm. Now consider the following statements:

S1: If $k=10$, it is enough if we store any $10$ points in the training dataset.

S2: If $k=10$, we need to store the entire dataset.

S3: The number of data points that we have to store increases as the size of $k$ increases.

S4: The number of data points that we have to store is independent of the value of $k$.

  1. S1 AND S3 ARE TRUE STATEMENTS
     
  2. S2 AND S4 ARE TRUE STATEMENTS
     
  3. S1 ALONE IS A TRUE STATEMENT
     
  4. S3 ALONE IS A TRUE STATEMENT

1 Answer

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The entire training dataset has to be stored in memory. For predicting the label of a test point, we have to perform the following steps:

  • Compute the distance of the test point from each training point.
     
  • Sort the training data points in ascending order of distance.
     
  • Choose the first $k$ points in this sequence.
     
  • Return that label which garners the maximum vote among these $k$ neighbors.
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