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The Linear Support Vector Classifier (Linear SVC) algorithm is a popular machine learning algorithm used for binary classification problems.Unlike traditional SVM, Linear SVC uses a linear kernel function to transform the data into a higher-dimensional space, making it easier to separate the data into two classes
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The Linear Support Vector Classifier (Linear SVC) algorithm is a popular machine learning algorithm used for binary classification problems. It is a variant of the Support Vector Machine (SVM) algorithm, the Linear SVC algorithm works by finding the best hyperplane that maximizes the margin between the two classes of data. The edge is defined as the distance between the hyperplane and the closest data points from each class. By maximizing the margin, Linear SVC creates a decision boundary that is most likely to simplify well to new data. Unlike traditional SVM, Linear SVC uses a linear kernel function to transform the data into a higher-dimensional space, making it easier to separate the data into two classes
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