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  • Support vector machine - Wikipedia
    In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised max-margin models with associated learning algorithms that analyze data for classification and regression analysis
  • Support Vector Machine (SVM) Algorithm - GeeksforGeeks
    The key idea behind the SVM algorithm is to find the hyperplane that best separates two classes by maximizing the margin between them This margin is the distance from the hyperplane to the nearest data points (support vectors) on each side
  • What Is Support Vector Machine? | IBM
    A support vector machine (SVM) is a supervised machine learning algorithm that classifies data by finding an optimal line or hyperplane that maximizes the distance between each class in an N-dimensional space
  • Support Vector Machine (SVM) Explained: Components Types - Snowflake
    Support vector machines (SVMs) are algorithms used to help supervised machine learning models separate different categories of data by establishing clear boundaries between them As an SVM classifier, it’s designed to create decision boundaries for accurate classification
  • Support Vector Machine (SVM) Algorithm - Great Learning
    Support Vector Machine (SVM) is a supervised machine learning algorithm used for classification and regression tasks It is widely applied in fields like image recognition, text classification, and bioinformatics due to its efficiency in handling high-dimensional data
  • 11 Support Vector Machines – STAT 508 | Applied Data Mining and . . .
    Support vector machines are a class of statistical models first developed in the mid-1960s by Vladimir Vapnik In later years, the model has evolved considerably into one of the most flexible and effective machine learning tools available
  • Support Vector Machine (SVM) - Analytics Vidhya
    What is a Support Vector Machine (SVM)? A Support Vector Machine (SVM) is a machine learning algorithm used for classification and regression This finds the best line (or hyperplane) to separate data into groups, maximizing the distance between the closest points (support vectors) of each group
  • What is a support vector machine (SVM)? - TechTarget
    A support vector machine (SVM) is a type of supervised learning algorithm used in machine learning to solve classification and regression tasks SVMs are particularly good at solving binary classification problems, which require classifying the elements of a data set into two groups




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