Can you differentiate between Logistic Regression and K-Nearest Neighbors (KNN) in terms of use case and functionality?
- LR is for classification, KNN for classification; LR uses probability, KNN uses distance
- LR is for classification, KNN for regression; LR uses distance, KNN uses probability
- LR is for classification, KNN for regression; LR uses probability, KNN uses distance
- LR is for regression, KNN for classification; LR uses distance, KNN uses probability
Logistic Regression is used for classification and models the probability of a binary outcome. KNN is also used for classification but works by considering the 'K' nearest data points. The fundamental difference lies in the approach: LR uses a logistic function, while KNN uses distance metrics.
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