This requires basic machine learning literacy — what kinds of problems can machine learning solve, and how to talk about those problems with data scientists. Linear regression and feature ...

Although [Vitor Fróis] is explaining linear regression because it relates to machine learning, the post and ... [Vitor] starts out with a great example: home prices (the dependent variable ...

This plugin enhances Elasticsearch’s query engine by two new aggregations, which utilize the index data during search as training data for estimating a linear regression model in ... a house of our ...

Machine learning ... example, sorting algorithms turn unordered data into data ordered by some criteria, often the numeric or alphabetical order of one or more fields in the data. Linear ...

linear regression with interactions can handle more complex data while retaining a high level of model interpretability. The goal of a machine learning regression problem is to predict a single ...

Air pollution is of high relevance to human health. In this study, multiple machine-learning (ML) models—linear regression, random forest (RF), AdaBoost, and neural networks (NNs)—were used to explore ...