In this video, we will learn about the K nearest neighbors with python. In KNN, K is the number of nearest neighbors. The number of neighbors is the core deciding factor. K is generally an odd number if the number of classes is 2. When K=1, then the algorithm is known as the nearest neighbor algorithm. This is the simplest case. Suppose P1 is the point, for which the label needs to predict. First, you find the one closest point to P1 and then the label of the nearest point assigned to P1.
#KNN #MachineLearning #ML
🔊 Watch till last for a detailed description
02:05 How does the KNN algorithm work?
05:18 Curse of dimensionality
08:40 Classifier building in python and scikit-learn
13:51 Generating model for K=3
19:11 Standardization in sklearn
23:29 Cross-validation
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