Nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables. The data are fitted by a method of successive approximations.
Principle component analysis is a powerful technique when you have linear data sets. Of course when entering the problem of I don’t know if my data is linear or not needs explorationref.
A support-vector machine constructs a hyperplane or set of hyperplanes in a high- or infinite-dimensional space, which can be used for classification, regression, or other tasks like outliers detection
An interconnected group of natural or artificial neurons that uses a mathematical or computational model for information processing based on a connectionistic approach to computation.
The k-nearest neighbors (KNN) algorithm is a simple, easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems