Nodes for building dictionary-based classifiers for text documents. Using a set of labeled sample documents, one can build a dictionary and use it to classify uncategorized documents. Typical use cases for text classification are e.g. automated email spam detection, language identification, or sentiment analysis.
This category contains 7 nodes.
Reader for Palladian’s dataset format.
Learner for a dictionary-based text classifier for categorizing text documents.
Different pruning methods for Palladian text classifier models.
This node allows the deserialization of a trained Text Classifier model.
Converts a text classifier model to a table.
This node allows serializing a trained Text Classifier model, so that it can be used programmatically within Palladian.
Predictor for a dictionary-based text classifier for categorizing text documents.
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