Our main contribution is the development of a new soft sparse multinomial logistic regression model which exploits both hard and soft labels. In our terminology, these labels respectively correspond ...

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you ...

Multinomial Naïve Bayes is a good match for our data for several reasons: There are several other machine learning models including logistic regression ... s performance by plotting the confusion ...

Multilable fast inference classifiers (Ridge Regression and MLP) for NLPs with Sentence Embedder, K-Fold, Bootstrap and Boosting. NOTE: since the MLP (fully connected NN) Classifier was too heavy to ...

This project is implementation of a classififer that predicts the probable outcome for the best crop to plant in a given region and area given a few climatic and chemical conditions available in the ...

Meta AI has released Llama Prompt Ops, a Python package designed to streamline the process of adapting prompts for Llama models. This open-source tool is built to help developers and researchers ...