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Python KNN Algorithm Tutorial | Python for Big Data Analytics | Edureka
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K- Near Neighbors (KNN) is a simple algorithm in pattern recognition. It is a non-paramentric method, which measures distance between the scenario of a single query and a set of scenarios in a data set. It is mainly used for classification and regression. Following are the topics covered in the video:
1. KNN Algorithm (Example)
2. KNN Algorithm- Significance
3. KNN Algorithm- Pros & Cons
4. Building the Classifier
5. Executing the Classifier
6. Testing a Classifier
7. Clustering
Related Posts:
Edureka is a New Age e-learning platform that provides Instructor-Led Live Online classes for learners who would prefer a hassle free and self-paced learning environment, accessible from any part of the world.
The topics, related to KNN Algorithm have been widely covered in our course ‘Python for Big Data Analytics’.
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1. KNN Algorithm (Example)
2. KNN Algorithm- Significance
3. KNN Algorithm- Pros & Cons
4. Building the Classifier
5. Executing the Classifier
6. Testing a Classifier
7. Clustering
Related Posts:
Edureka is a New Age e-learning platform that provides Instructor-Led Live Online classes for learners who would prefer a hassle free and self-paced learning environment, accessible from any part of the world.
The topics, related to KNN Algorithm have been widely covered in our course ‘Python for Big Data Analytics’.
Call us at US: 1800 275 9730 (toll free) or India: +91-8880862004
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