Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis ...

The proposed model gains insight into factors causing flight delays, cancellations and the relationship between departure and arrival delay using exploratory data analysis. In addition, Random Forest ...

Degradation models of battery are required for reliable, optimized and safe deployment of battery systems in different large scale applications, such as grid-integrated energy storage systems.

This project is part of a university assignment aimed at building a machine learning model to classify hotel reservations. The project encompasses several stages, including data preparation, data ...

In practice, exploratory data analysis combines graphics and descriptive statistics. In a highly cited book chapter, Tukey uses R to explore the 1990s Vietnamese economy with histograms, kernel ...

Objectives To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need ...

Traditional ridership forecast models such as 4-step and activity-based models rely on U.S. Census commuting data and large expensive travel surveys. This data can tell us where people live, where ...