Logistic Regression is another popular and versatile algorithm that can be used for text classification. It is a linear model that predicts the probability of a text belonging to a class by using ...

Some optimization algorithms also adapt the learning rates of the model parameters by looking at the gradient history (AdaGrad, RMSProp, and Adam). Classification algorithms can find solutions to ...

For the characteristics of real-time and large data volume, there are some relatively mature algorithms that can process a large amount of data in real time, thus affecting the classification model by ...

Abstract: For the traditional big data classification models and algorithms that have the drawback of long processing time, the use of intelligent algorithms to model identification of multivariable ...

The aim of this study was to develop a model that can accurately predict the likelihood of developing diabetes in patients with the greatest amount of precision. Classification algorithms are widely ...

This document provides an overview of common classification algorithms, their working principles, advantages, disadvantages, and typical use cases. Supervised learning is a machine learning approach ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic ...