Figure 1
From: A machine learning approach to analyse ozone concentration in metropolitan area of Lima, Peru
Architecture machine learning: Linear regression, support vector regression, decision trees, random forest, and multilayer perceptron. Data tasks: the data related to the ozone concentration in the winter season of 2017, 2018 and 2019 are organized. Individual tasks: machine learning models are applied to data that was previously organized. Common tasks: the prediction is made and the errors of each model are calculated using performance metrics.
