K-Nearest Neighbors is a machine learning algorithm that classifies new data points based on the majority class of its k nearest neighbors. It finds the k closest training examples in the feature space, counts the numbers of each class, and assigns the new point to the majority class. The objective is to learn a function that maps inputs to outputs based on similarity. It performs well when the distance between points is meaningful, such as with Euclidean distance. To apply it, one selects the number of neighbors k and a distance metric to find the closest points and classify new data.

1. What is K-Nearest Neighbors?
K-Nearest Neighbors is a supervised
machine learning algorithm
composed of a specified labeled
dataset accommodating training sets
(x, y) and would like to represent the
correlation between x and y

2. 1.
2.
3.
New test point is categorized by
greater number of votes of its
neighbors
The test point is allocated to the
category most available among
its k nearest neighbors
If k=1, then new point is
allocated to the category of its
only nearest neighbor
Objective of KNN Algorithm
KNN finds out a function
𝒉: 𝒙 → 𝒚 hence for a new
test point 𝒙, 𝐡(𝐱)can
assertively deduce the
equivalent output y

3. The feat of KNN classifier is
mostly hinges on the
distance metric employed to
recognize the k nearest
neighbors of a test point
1 Euclidean Distance
2 Manhattan Distance
3 Minkowski Distance
4 Hamming Distance

4. x
y
𝑥1 𝑥2
𝑦1
𝑦2
𝑃1 𝑥1, 𝑦1
𝑃2 𝑥2, 𝑦2
Euclidean Distance (d) = 𝑥2 − 𝑥1
2 + 𝑦2 − 𝑦1
2
The most commonly employed distance is the Euclidean Distance !!

5. Choose no. of Nearest Neighbors (k)
Calculates d between x & k
Select a Distance Metric (d)
Counts data points for classes
Allocates x to the class of max neighbors
HOW
KNN
ALGORITHM
WORKS
KNN
Classifier

6. +++
If k = 3 the test sample (green
polygon) is allocated to the
category of blue circle
If k = 5 then the test sample is
assigned to the category of
yellow square

7. We will define a KNN
Classifier to classify three
types of Flowers from
the Iris Data Set !
Let’s demonstrate k
nearest neighbors in
google colab !!!