A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Building on the above findings, we investigated the differences in size-resolved exhaled aerosol emissions and the associated phonetic variations for conveying identical semantics across eight ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1 ...

Random Forest models, by aggregating the predictions of multiple trees, generally produce more robust and accurate predictions compared to a single decision tree. The Random Forest algorithm is a ...

This multi-phase project identifies key satisfaction drivers and provides actionable insights to improve customer experience using statistical analysis and machine learning models, including logistic ...

In addition, a genetic algorithm is used to optimize the parameters of the random forest model for early warning of grid fault occurrence. The experimental results demonstrate that the proposed GA-RF ...

Random forest regression is most often used with data that has strictly numeric predictor variables. It is possible to use random forest regression with mixed categorical and numeric data, by using ...

The Data Science Lab Random Forest Regression and Bagging Regression Using C# Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression ...