In a situation where the data is densely packed in some regions and sparse in others, how would the choice of K and distance metric influence the results, and what would be the best approach?
- Choose a fixed K and Euclidean distance
- Choose a large K and any distance metric
- Choose a small K and ignore distance metric
- Choose an appropriate K and distance metric, considering data distribution
Considering the data distribution and choosing an appropriate value of K and distance metric can help address the issue of varying data density in KNN.
Loading...
Related Quiz
- CNNs are particularly effective for image data due to their ability to preserve the ________ structure of the data.
- Which layer in a CNN is responsible for reducing the spatial dimensions of the input data?
- Clustering is a common task in __________ learning, where data is grouped based on inherent similarities without the use of labels.
- Which algorithm can be used for both regression and classification tasks, and is particularly well-suited for dealing with large data sets and high-dimensional spaces?
- Explain how the learning agent interacts with the environment in Reinforcement Learning.