This quiz consists of questions and answers on Support Vector Machine (SVM). This is a practice test (objective questions and answers) which can be useful when preparing for interviews. The questions in this and upcoming practice tests could prove to be useful, primarily, for data scientist or machine learning interns / freshers / beginners. The questions are focused around some of the following areas:
- Introduction to SVM
- Types of SVM such as maximum-margin classifier, soft-margin classifier, support vector machine
Some of the key SVM concepts to understand while preparing for interview are following:
- SVM concepts and objective functions
- SVM kernel functions, tricks
- Concepts of C and Gamma value
- Scikit learn libraries for training SVM models
Here are some of the useful posts on SVM you could read for understanding SVM in a better manner:
- SVM Algorithm as Maximum Margin Classifier
- SVM Classifier using Scikit Learn – Code Examples
- SVM – Understanding C Value with Code Examples
- SVM as Soft Margin Classifier and C Value
- Machine Learning – SVM Kernel Trick Example
- SVM RBF Kernel Parameters with Code Examples
Support Vector Machine – Practice Test
Support vector machine (SVM) is a _________ classifier?
SVM can be used to solve ___________ problems.
SVM is a ___________ learning algorithm
SVM is termed as ________ classifier
The training examples closest to the separating hyperplane are called as _______
Which of the following is a type of SVM?
The goal of the SVM is to __________
When using R, which of the following package is used for SVM?
Based on the form of error function, SVM models can be classified into which of the following?
In case of classification problem, which of the following may be used?
Which of the following SVM model can be used to detect the outliers?
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