A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning ...

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, ...

Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...

The classification of tree species through remote sensing data is of great significance to monitoring forest disturbances, biodiversity assessment, and carbon estimation. The dense time series and a ...

Using the Student Performance dataset from the UCI Machine Learning Repository, the study applies multiple decision tree variants, including C4.5, CART, Random Forest, and Gradient Boosted Trees. The ...