Model-based clustering provides a principled way of developing clustering methods. We develop a new model-based clustering methods for count data. The method combines clustering and variable selection ...

Objectives: To develop a diagnostic prediction model for rapidly progressive central precocious puberty (RP-CPP) and evaluate the contribution of osteocalcin(OC) to the model. Methods: For a total of ...

Abstract: This paper focuses on the design and application of a multivariate financial time series prediction model based on the Transformer, with the goal of enhancing forecast accuracy and ...

In this repository, we present the code of "CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting". conda create -n cmamba ...

Abstract: To address the challenges of traditional marine meteorological prediction methods, which struggle to effectively capture intervariable correlations in multivariate time series data and ...

Want to understand how multivariate linear regression really works under the hood? In this video, we build it from scratch in C++—no machine learning libraries, just raw code and linear algebra. Ideal ...