ABSTRACT: In this paper, an Optimal Predictive Modeling of Nonlinear Transformations “OPMNT” method has been developed while using Orthogonal Nonnegative Matrix Factorization “ONMF” with the ...

Abstract: Matrix factorization is a central paradigm in matrix completion and collaborative filtering. Low-rank factorizations have been extremely successful in reconstructing and generalizing ...

What is Singular Spectrum Analysis (SSA)? Singular Spectrum Analysis (SSA) is a non-parametric technique in machine learning used to analyze and forecast time series data. SSA decomposes a time series ...

Getting input from users is one of the first skills every Python programmer learns. Whether you’re building a console app, validating numeric data, or collecting values in a GUI, Python’s input() ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Click to share on X (Opens in new window) X Click to share on Facebook (Opens in new window) Facebook Michael ends up finding himself trapped on the roof of his school with the Agents closing in on ...

This is a translation of the MEMD (Multivariate Empirical Mode Decomposition) code from Matlab to Python. The Matlab code was developed by [1] and is freely available ...

Abstract: Multi-layered graphs are popular in mobility studies because transportation data include multiple modalities, such as railways, buses, and taxis. Another example of a multi-layered graph is ...

Automatic differentiation has transformed the development of machine learning models by eliminating complex, application-dependent gradient derivations. This transformation helps to calculate Jacobian ...

Click to share on X (Opens in new window) X Click to share on Facebook (Opens in new window) Facebook Given Shout’s business plan, it seems likely they will mount a new special edition Blu-ray of ...