What are the pros and cons of using SVM in classification tasks ?
The Support Vector Machine is a powerful algorithm for supervised learning that’s widely used in classification and regression. It is especially effective in high-dimensional space and is well known for its robustness when handling complex datasets. SVM, like other machine-learning algorithms, has strengths and weaknesses that affect its suitability for different tasks.Data Science Course in Pune
SVM’s ability to handle data with high dimensions is one of its most important advantages. SVM is able to perform exceptionally well in scenarios where the number features exceeds that of the samples. It is particularly useful for domains like text classification, bioinformatics, and image recognition.
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The Support Vector Machine is a powerful algorithm for supervised learning that’s widely used in classification and regression. It is especially effective in high-dimensional space and is well known for its robustness when handling complex datasets. SVM, like other machine-learning algorithms, has strengths and weaknesses that affect its suitability for different tasks.Data Science Course in Pune
SVM’s ability to handle data with high dimensions is one of its most important advantages. SVM is able to perform exceptionally well in scenarios where the number features exceeds that of the samples. It is particularly useful for domains like text classification, bioinformatics, and image recognition.
https://www.sevenmentor.co...
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