Linear regression is an excellent place to start when using machine learning to predict numbers. Combined with relevant features, it’s a slam dunk. Related content ...

There are dozens of machine learning algorithms, ranging in complexity from linear regression and logistic regression to deep neural networks and ensembles (combinations of other models). However ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...

Regression is one of the most common data science problem. It, therefore, finds its application in artificial intelligence and machine learning. Regression techniques are used in machine learning to ...

Quantitative Structure-Property Relationship (QSPR) modeling is one of the novel ways of predicting the physicochemical properties of a drug through its molecular descriptor (topological index (TI)).

Examples of discriminative models in machine learning include support vector machines, logistic regression, decision trees, and random forests. Differences Between Generative and Discriminative.

With the development of machine learning, the advantages of causal learning over statistics have been pointed out. This paper investigates whether causal logic can significantly improve machine ...