SVM
- noun
- Specialized
- Experiment 1 is focused on choosing the best kernel for the SVM classifier during the training and testing phases.
- SVM classifier
- kernel for the SVM
- SVM model
More modern technologies now would use SVM's Ada boost boosting tech technologies for classification.
- More modern technologies now would use SVM's Ada boost boosting tech technologies for classification.
Examples
-
Several classification algorithms were tested, with SVM being the one with the highest accuracy.
Academic text (2016) -
We also optimized the choice of kernel for the SVM-based classifier during the training and testing phases.
Academic text (2016) -
And it turns out that you can apply an SVM with the following kernel.
-
You can take SVM and you get kernel SVM.
-
Therefore, the existing methods do not allow implementing SVM in data that cannot be classified by linear decision functions.
Academic text (2018) -
A similar trend was also observed for SVM, with the optimal accuracy also at 12 x 12 sampling resolution.
Academic text (2017) -
A parameter to evaluate for the SVM models was the cost-function term C.
Academic text (2018) -
Two supervised learning algorithms, RF and SVM, were used to train and test the datasets at different resolutions.
Academic text (2017) -
The authors used an SVM-based classifier for training and testing, resulting in a classification accuracy of 83.77%.
Academic text (2016) -
The researchers applied an SVM to distinguish between different categories of data with high precision.
Synonyms
A computer program that learns from examples to put data into groups or predict values
A computer method that finds a clear boundary to separate different groups of data
How Advanced
Surface Forms
Morphology
Etymology
The word SVM stands for Support Vector Machine, and the name is a helpful memory hook: support means 'to hold', vector means 'arrow' or 'direction', and machine means 'tool'. So an SVM is a tool that uses a few key points and directions to find a clear border that separates different groups of data.