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1. www.javatpoint.com › k-nearest-neighbor-algorithmK-Nearest Neighbor (KNN) Algorithm for Machine Learning

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   Learn how to use KNN, a simple and non-parametric algorithm based on similarity measure, for classification and regression problems. See the steps, advantages, disadvantages and Python implementation of KNN with an example of car manufacturer company.

2. www.geeksforgeeks.org › k-nearest-neighboursK-Nearest Neighbor(KNN) Algorithm - GeeksforGeeks

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   1 day ago · Learn about the K-Nearest Neighbor (KNN) algorithm, a supervised machine learning method for classification and regression problems. Find out how it works, what distance metrics it uses, and why it is easy to implement and adapt.

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3. towardsdatascience.com › machine-learning-basicsMachine Learning Basics with the K-Nearest Neighbors ...

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   Sep 10, 2018 · Learn how to use the k-nearest neighbors (KNN) algorithm for classification and regression problems. The algorithm is simple, versatile, and based on the assumption that similar things are near to each other.

4. www.ibm.com › topics › knnWhat is the k-nearest neighbors algorithm? | IBM

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   The k-nearest neighbors (KNN) algorithm is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point. It is one of the popular and simplest classification and regression classifiers used in machine learning today.

5. machinelearningmastery.com › k-nearest-neighborsK-Nearest Neighbors for Machine Learning

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   Aug 15, 2020 · KNN has no model other than storing the entire dataset, so there is no learning required. Efficient implementations can store the data using complex data structures like k-d trees to make look-up and matching of new patterns during prediction efficient.

6. www.w3schools.com › python › python_ml_knnPython Machine Learning - K-nearest neighbors (KNN) - W3Schools

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   Learn how to use KNN, a simple and versatile algorithm for classification or regression tasks, with Python code and examples. See how different values of K affect the results and visualize the data points and predictions.

7. People also ask

   What is the kNN algorithm?

   • The k-nearest neighbors (KNN) algorithm is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point. It is one of the popular and simplest classification and regression classifiers used in machine learning today.

   What is the k-nearest neighbors algorithm? | IBM

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   What is KNN in machine learning?

   • KNN is one of the most basic yet essential classification algorithms in machine learning. It belongs to the supervised learning domain and finds intense application in pattern recognition, data mining, and intrusion detection.

   K-Nearest Neighbor(KNN) Algorithm - GeeksforGeeks

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   Is KNN a nonparametric machine learning algorithm?

   • As such KNN is referred to as a non-parametric machine learning algorithm. KNN can be used for regression and classification problems. When KNN is used for regression problems the prediction is based on the mean or the median of the K-most similar instances.

   K-Nearest Neighbors for Machine Learning

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   Is KNN a lazy learning algorithm?

   • As such, KNN is often referred to as a lazy learning algorithm. Non-Parametric: KNN makes no assumptions about the functional form of the problem being solved. As such KNN is referred to as a non-parametric machine learning algorithm. KNN can be used for regression and classification problems.

   K-Nearest Neighbors for Machine Learning

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8. www.analyticsvidhya.com › blog › 2018Guide to K-Nearest Neighbors Algorithm in Machine Learning

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   What is KNN (K-Nearest Neighbor) Algorithm in Machine Learning? The K-Nearest Neighbors (KNN) algorithm is a popular machine learning technique used for classification and regression tasks. It relies on the idea that similar data points tend to have similar labels or values.