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Feature Description
A Support Vector Machine (SVM) is a machine learning algorithm used for classification tasks. It works by finding a hyperplane in the feature space that best separates the data points belonging to different classes. In our case, the data points are features extracted from images of cats and dogs, and the SVM aims to create a decision boundary that accurately classifies new images.
Use Case
Automatically identifying animals in images has numerous applications. An animal shelter could use SVM classification to automate pet categorization on their website, allowing potential adopters to easily find cats or dogs. Similarly, wildlife conservation efforts could benefit from SVM-based image classification to monitor specific animal populations.
Benefits
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Priority
High
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