August 12, 2020
KNN Review
Data with n features can be conceptualized as points lying in n-dimensional space.
Data points can be compared using a distance formula.
A point with an unknown class can be classified using K-Nearest Neighbors.
To verify the effectiveness of a classifier, data with known classes can be split into a training set and a validation set.
Classifiers have parameters that can be tuned to increase effectiveness.
Python’s sklearn can be used for many classification and machine learning algorithms.
