The project employs two main algorithms: Linear Regression and Decision Trees ... pressure, etc.) to predict precipitation levels. By analyzing past weather data, the model provides precipitation ...

Abstract: Weather factors such as temperature and rainfall in residential areas and tourist destinations affect traffic flow on the surrounding roads. In this study, we attempt to find new knowledge ...

From the weather aspect, this paper aims to build weather analysis program to predict rice cultivation time ... for the past 1 year and using the obtained data to build a regression model using ...

The business needs to improve their strategy, towards end and start of the year, considering the weather and season ... of training and test data are 83.6 and 81.6 respactively, which is quite good.

Causal forecasting attempts to predict a variable by trying to explain what factors cause it to change. For example, a causal model ... use of linear regression depends on the data and the goals ...

Investopedia / Nez Riaz Multiple linear regression ... predict an outcome based on information provided on multiple explanatory variables. Still, the model is not always perfectly accurate, as ...

Metabolome data were obtained from tomato leaves and used as variables for linear regression with the least absolute shrinkage and selection operator (LASSO) for prediction. The constructed model ...