Can we use svm for text classification?

From Texts to Vectors It can be applied to any kind of vectors which encode any kind of data. This means that in order to leverage the power of svm text classification, texts have to be transformed into vectors.

Can svm be used for multi class classification?

In its most basic type, SVM doesn’t support multiclass classification. For multiclass classification, the same principle is utilized after breaking down the multi-classification problem into smaller subproblems, all of which are binary classification problems.

Which algorithm is best for multiclass text classification?

Linear Support Vector Machine is widely regarded as one of the best text classification algorithms. We achieve a higher accuracy score of 79% which is 5% improvement over Naive Bayes.

What is multi class text classification?

Text classification (multiclass) With the aim to classify future complaints based on its content, we used different machine learning algorithms can make more accurate predictions (i.e., classify the complaint in one of the product categories).

Why SVM is used for classification?

The goal of the SVM algorithm is to create the best line or decision boundary that can segregate n-dimensional space into classes so that we can easily put the new data point in the correct category in the future. SVM algorithm can be used for Face detection, image classification, text categorization, etc.

What is the best classifier for text classification?

How SVM is used for classification?

SVM is a supervised machine learning algorithm which can be used for classification or regression problems. It uses a technique called the kernel trick to transform your data and then based on these transformations it finds an optimal boundary between the possible outputs.

Which model is best for text classification?

Which model is best for multiclass classification?

Popular algorithms that can be used for multi-class classification include:

• k-Nearest Neighbors.
• Decision Trees.
• Naive Bayes.
• Random Forest.
• Gradient Boosting.

Which algorithm is best for text classification?