Is SVM regression or classification?
Is SVM regression or classification?
SVM or Support Vector Machine is a linear model for classification and regression problems. It can solve linear and non-linear problems and work well for many practical problems. The idea of SVM is simple: The algorithm creates a line or a hyperplane which separates the data into classes.
What is LIBSVM format?
MLlib supports reading training examples stored in LIBSVM format, which is the default format used by LIBSVM and LIBLINEAR . It is a text format in which each line represents a labeled sparse feature vector using the following format: label index1:value1 index2:value2 …
Is SVM used for both classification and regression problem?
“Support Vector Machine” (SVM) is a supervised machine learning algorithm that can be used for both classification or regression challenges. However, it is mostly used in classification problems.
Why is SVM better than linear regression?
SVM tries to finds the “best” margin (distance between the line and the support vectors) that separates the classes and this reduces the risk of error on the data, while logistic regression does not, instead it can have different decision boundaries with different weights that are near the optimal point.
Is SVM a classification algorithm?
How does SVM do regression?
Support Vector Regression is a supervised learning algorithm that is used to predict discrete values. Support Vector Regression uses the same principle as the SVMs. The basic idea behind SVR is to find the best fit line. In SVR, the best fit line is the hyperplane that has the maximum number of points.
What is Liblinear and LIBSVM?
LIBSVM and LIBLINEAR are two popular open source machine learning libraries, both developed at the National Taiwan University and both written in C++ though with a C API.
What are the types of SVM?
According to the form of this error function, SVM models can be classified into four distinct groups: Classification SVM type 1 (also known as C-SVM classification) Classification SVM type 2 (also known as nu-SVM classification) Regression SVM type 1 (also known as epsilon-SVM regression)