The python module sklearn.svm.SVR is a part of the scikit-learn library and provides the functionality to perform Support Vector Regression (SVR). SVR is a supervised machine learning algorithm that can be used for regression tasks. It works by finding a hyperplane in a higher-dimensional space that approximates the target values as closely as possible. SVR is commonly used for solving regression problems in various domain contexts, such as finance, medicine, and computer vision. The sklearn.svm.SVR module offers several options for parameter tuning and customization, allowing users to adapt the algorithm to their specific regression problem.
Python SVR - 60 examples found. These are the top rated real world Python examples of sklearn.svm.SVR extracted from open source projects. You can rate examples to help us improve the quality of examples.