What is the main principle behind the K-Nearest Neighbors algorithm?
- Calculating correlations
- Finding nearest points
- Grouping similar objects
- Minimizing error
The main principle of KNN is to classify a new object by assigning it to the most common class among its K nearest neighbors.
Loading...
Related Quiz
- Game-playing agents, like those used in board games or video games, often use ________ learning to optimize their strategies.
- When a Decision Tree is too complex and fits the training data too well, __________ techniques can be applied to simplify the model.
- What distinguishes autoencoders from other traditional neural networks in terms of their architecture?
- Dimensionality reduction is often used to overcome the ___________ problem, where having too many features relative to the number of observations can lead to overfitting.
- You're working with a large dataset of facial images. You want to reduce the dimensionality of the images while preserving their primary features for facial recognition. Which neural network structure would you employ?