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Create a new text classifier: Go to the dashboard, then click Create a Model, and choose Classifier: Upload training data: Next, you'll need to upload the data that you want to use as examples for training your model. Define the tags for your model: Tag data to train the classifier:
Text classification or Text Categorization is the activity of labeling natural language texts with relevant categories from a predefined set. In laymen terms, text classification is a process of extracting generic tags from unstructured text. These generic tags come from a set of pre-defined categories.
Text classification or Text Categorization is the activity of labeling natural language texts with relevant categories from a predefined set. In laymen terms, text classification is a process of extracting generic tags from unstructured text. These generic tags come from a set of pre-defined categories.
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.
It exclusively compares the input text with the training texts included in the model. In other words, when you train a model you associate each category to sample texts, so that when you enter a text to classify, the system will compare it with the examples and will determine which one is the nearest.
Expectation maximization (EM) Naive Bayes classifier. Tfidf. Instantaneously trained neural networks. Latent semantic indexing. Support vector machines (SVM) Artificial neural network. K-nearest neighbor algorithms.
Broke the documents in list of words. Removed stop words, punctuations. Performed stemming. Replaced numerical values with '#sum#' to reduce vocabulary size. Transformed the documents into TF-IDF vectors.
Create a new text classifier: Go to the dashboard, then click Create a Model, and choose Classifier: Upload training data: Next, you'll need to upload the data that you want to use as examples for training your model. Define the tags for your model: Tag data to train the classifier:
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