How does the complexity of the task affect the choice of algorithm? How does the interpretability requirement affect the choice of algorithm?

Our experiments have shown that both approaches can interact with LLMs successfully to classify text—if certain criteria are met ... Mar 18, 2025 ... Text classification is an AI technique that allows you to use an algorithm to sort text data into categories. This technology is an important ... Feb 28, 2024 ... Text Classification. Text classification analyses the text and identifies categories for the content with a confidence score. Text ... In this paper, a brief overview of text classification algorithms is discussed. This overview covers different text feature extractions, dimensionality ... Use the text classification models to classify a set of words from a resource based on three text classification algorithms: Bag-of-Words, N-Gram, and Text ... Jun 8, 2021 ... A compression algorithm has some knowledge of the distribution of words in a corpus. It can thus be used to classify documents. Existing statistical text learning algorithms can be trained to approximately classify documents, given a sufficient set of labeled training examples. These ... Dec 10, 2022 ... Classifying Text Using ML.NET and C# · Load the data from a TSV file · Train a text classification model · Generate evaluation metrics for the ... This paper compares the performance of ten such approaches (five lexicon-based, five machine learning algorithms) across 41 social media datasets. Evaluate with Argilla¶. Now, we can start the annotation process. Just open the dataset in the Argilla UI and start annotating the records. If the suggestions ...