Abstract: In the context of earthquake prediction, the purpose of this study is to evaluate the accuracy of the Linear Regression Algorithm in comparison to Poisson regression. The linear regression ...

To develop speaker adaptation algorithms for deep neural network (DNN) that are suitable for large-scale online deployment, it is desirable that the adaptation model be represented in a compact form ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee's bank account balance based on age, height, annual income, ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

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This is a machine learning-based web application built with Flask that predicts the estimated salary of an individual based on their: Years of Experience Education Level Location Previous Salary The ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

A machine learning random forest regression system predicts a single numeric value. A random forest is an ensemble (collection) of simple decision tree regressors that have been trained on different ...