Model-based clustering based on parameterized finite Gaussian mixture models. Models are estimated by EM algorithm initialized by hierarchical model-based agglomerative clustering. The optimal model ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

New York – September 2, 2025 – With the start of the broadcast and football seasons this month, Nielsen today shared several updates for reporters covering TV, as the industry is adopting Nielsen’s ...

This study introduces a more flexible approach by employing the fixed effects negative binomial model to address challenges associated with outliers and dispersion. Unlike previous studies that ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Abstract: The Gaussian Mixture Model (GMM) is widely used in anomaly detection due to its flexibility in handling complex data distributions and its soft classification mechanism. However, its ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

What if the tools you already use could do more than you ever imagined? Picture this: you’re working on a massive dataset in Excel, trying to make sense of endless rows and columns. It’s slow, ...

Here we describe the process of generating the clustering analysis from cells with TDP-43 knockdown and the activation of TDP-REG reporter as in our manuscript (Fig.S5F) To use, orient to the folder ...