The correct answer is C. Support Vector Machine is a geometric model.
A support vector machine (SVM) is a supervised machine learning model that can be used for classification and regression tasks. SVMs work by finding a hyperplane in a high-dimensional space that separates the data points into two classes. The hyperplane is chosen such that it is as far as possible from any data point, which means that it is a good separator of the two classes.
SVMs are often used for classification tasks, such as spam filtering and image classification. They can also be used for regression tasks, such as predicting house prices or stock prices.
SVMs are a powerful machine learning model that can be used for a variety of tasks. They are often used in cases where accuracy is important, such as spam filtering and image classification.
Here is a brief explanation of each option:
- A logical model is a model that is based on logic. Logical models are often used in artificial intelligence and computer science.
- A probabilistic model is a model that is based on probability. Probabilistic models are often used in statistics and machine learning.
- A geometric model is a model that is based on geometry. Geometric models are often used in computer graphics and engineering.
I hope this helps!