A complete ML project that explores feature engineering, model training (Decision Tree, Random Forest, Gradient Boosting), and model interpretation using SHAP and LIME. This project contributed ...

Machine Learning / Data mining project in python. In this project, various classification algorithms such as Decision Tree, k-nearest neighbours, random forest and support vector machine have been ...

To optimize satellite-based monitoring, we train a Random Forest classifier on the train dataset to map summergreen and evergreen forest resulting in accuracies of 63% for early summer, 89% for peak ...

A 12-foot-long python weighing approximately 20 kilograms was rescued by locals of Chandra Village in the Nagarbera Riverine Range under the West Kamrup Division on Friday. India slams Bangladesh ...

From aging trees to a nonexistent workforce, many of Alabama’s urban forests are facing major challenges. Over the next five years, the Alabama Cooperative Extension System’s Green Up Alabama program ...

All basic statistical procedures were performed with the SPSS version 26.0. We used the one-sample Kolmogorov ... employed a random forest modeling approach to perform a binary classification task.

A sample might be selected from a population in many ways. One is the stratified random sampling method. Stratified random sampling involves dividing the entire population into homogeneous groups ...