KNN Start

vishnoitanuj · Nov 6, 2018 · 907cd6c · 907cd6c
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diff --git a/Part 3 - Classification/Section 15 - K-Nearest Neighbors (K-NN)/KNN.py b/Part 3 - Classification/Section 15 - K-Nearest Neighbors (K-NN)/KNN.py
diff --git a/Part 3 - Classification/Section 15 - K-Nearest Neighbors (K-NN)/README.md b/Part 3 - Classification/Section 15 - K-Nearest Neighbors (K-NN)/README.md
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+# K-Nearest Neighbour
+
+Step 1: Choose the number of K neighbours (generally taken to be 5).
+Step 2: Take the K nearest neighbours of the new data point, according to the Euclidean distance.
+Step 3: Among these K neighbours, count the number of data points in each category.
+Step 4: Assign the new data point to the category where you counted the most neighbours.