What are the disadvantages of Logistic Regression?

Measuring and Mitigating Unintended Bias in Text Classification · Abstract · Research Areas. Natural Language Processing · Responsible AI. Meet the teams ... We introduce an algorithm for learning from labeled and unlabeled documents based on the combination of Expectation-Maximization (EM) and a naive Bayes ... Apr 4, 2019 ... In this study, we propose a new approach which combines rule-based features and knowledge-guided deep learning models for effective disease classification. May 25, 2016 ... Title:Adversarial Training Methods for Semi-Supervised Text Classification ... Abstract:Adversarial training provides a means of regularizing ... ... classification result. T This method is a classification enhancement method that can classify patent text alone or enhance the accuracy of various types of ... Aug 9, 2024 ... This study aimed to evaluate their performances on social media-based health-related text classification tasks. In this module, we will learn about the different types of machine learning that exist and the operational steps of building a supervised machine learning ... To help middle school students explore Artificial Intelligence (AI), we built a text classifier extension into a block-based programming interface using ... 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. The AutoKeras TextClassifier is quite flexible for the data format. For the text, the input data should be one-dimensional.