MLGrind - Master Machine Learning

Why this matters:

Tests understanding of distance-based algorithms – commonly asked to evaluate algorithmic thinking.

KNN is a non-parametric algorithm that classifies new data points based on the majority class of its k nearest neighbors in the training set.

Your implementation should:

Store the training data

Calculate Euclidean distances

Find k nearest neighbors

Return the majority class

Input:

X_train = [[0,0], [1,1]], y_train = [0, 1], X_test = [[0.5, 0.5]], k=1

Output:

[0]

Explanation:

With k=1, returns the class of the single nearest neighbor

K-Nearest Neighbors Classifier