Your modeling efforts are going to be fruitless. This catch is not specific to linear regression. It applies to any machine learning model in any domain — if the features available aren’t ...

Machine Learning, a subdomain of Artificial intelligence, is a pervasive technology that would mold how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox ...

In this context, machine learning ... because the cLogP model is an incremental model that relies on substructure contributions to the overall cLogP. Therefore the contributions are linear and ...

In computational chemistry and chemoinformatics, the support vector machine (SVM) algorithm is among the most widely used machine learning methods for the ... relevant features of classification and ...

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 ...

In recent years, there has been a rapid growth in the use of machine learning in material science. Conventionally, a trained predictive model describes a scalar ... This is an extension of kernel ...