It then shakes the claim otherwise made in IMF programmes that social spending will be protected, given the IMF programme ...
Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.
A hybrid modeling framework to optimize Chinese hamster ovary cell cultures for monoclonal antibody (mAb) production reduces the number of modeling parameters needed while returning results that ...
Aim: To determine how EMG, anthropometric, and psychological factors, and physical activity levels affect isokinetic peak torque performance (IPT) of multiple set exercise sessions. Methods: 20 ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
Abstract: Learning a function from input and output data pairs is one of the most fundamental tasks in machine learning. In this work, we propose a generalization of the Canonical Polyadic ...
Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets ...
Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on this powerful machine learning technique used to predict a single numeric value. A regression problem is one ...
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