SVM is a binary classifier based on supervised learning that outperforms other classifiers. SVM distinguishes between two classes by building a high-dimensional feature space hyperplane that can be utilized for classification.
SVM, or Support Vector Machine, is a linear model that can be used to solve classification and regression issues. It can solve linear and nonlinear problems and is useful for a wide range of practical applications. The concept of SVM is straightforward: The method draws a line or a hyperplane to divide the data into classes.
SVM, or Support Vector Machine, is a linear model that can be used to solve classification and regression issues. It can solve linear and nonlinear problems and is useful for a wide range of practical applications. The concept of SVM is straightforward: The method draws a line or a hyperplane to divide the data into classes.
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Muhammad Fahad Bashir
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Explained the concept easily
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Pradeep Kumar Kaushik
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Please give me iris,csv file.
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Ankit Malik
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where is the finaldata.csv
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Vimal Bhatt
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great learning plateform kushal sir is really too good
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