KNearest

Six methods to measure the effect of the number of neighbors on KNN model evaluationContinue reading on Towards Data Science » Six methods to measure the effect of the number of neighbors on KNN model evaluationContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners,…

Subdividing the Subsurface Based on Well Log MeasurementsPhoto by Johnson Wang on Unsplashk-Nearest Neighbors (kNN) is a popular non-parametric supervised machine learning algorithm that can be applied to both classification and regression-based problems. It is easy to implement in Python and easy to understand which makes it a great algorithm to start learning about when you start your machine-learning journey.Within this article, we will cover how the kNN algorithm works and how to apply it to well log data using…

Machine LearningWith hands-on case study walkthroughsPhoto by Fabrice Villard on UnsplashUnlike linear models and SVM (see Part 1), some machine learning models are really complex to learn from their mathematical formulation. Fortunately, they can be understood by following a step-by-step process they execute on a small dummy dataset. This way, you can uncover machine learning models under the hood without the “math bottleneck”.You will learn three more models in this story after Part 1: K-Nearest Neighbors (KNN), Naive…