Support Vector Machine
A Support Vector Machine (SVM) is a supervised learning algorithm that finds the hyperplane which best separates classes of data by maximizing the margin between them, and can be extended to nonlinear boundaries using the kernel trick.
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Glossary Terms(3)
Support Vector Machine
A Support Vector Machine (SVM) is a supervised learning algorithm that finds the hyperplane which best separates classes of data by maximizing the margin betwe…
Naive Bayes Classifier
A Naive Bayes classifier is a probabilistic machine learning algorithm based on Bayes' theorem that predicts a class by assuming all input features are conditi…
K-Nearest Neighbors
K-Nearest Neighbors (KNN) is a simple, non-parametric supervised learning algorithm that classifies or predicts a new data point based on the majority label or…