In this paper we present CatBoost, a new open-sourced gradient boosting library that
successfully handles categorical features and outperforms existing publicly available …

Real-time predictive modelling with desired accuracy is highly expected in industrial artificial
intelligence (IAI), where neural networks play a key role. Neural networks in IAI require …

In molecular design, material design, process design, and process control, it is important not
only to construct a model with high predictive ability between explanatory features x and …

This paper presents a novel framework for intrusion detection specially designed for
cyberattacks, such as Denial-of-Service, Distributed Denial-of-Service, Distributed Reflection …

Abstract Purpose To predict the Fuhrman grade of clear cell renal cell carcinoma (ccRCC)
with a machine learning classifier based on single-or three-phase computed tomography …

Background Stroke is an acute disorder and dysfunction of the focal neurological system that
has long been recognized as one of the leading causes of death and severe disability in …

For better stability, safety and water resource management in a dam, it is important to
evaluate the amount of seepage from the dam body. This research is focused on machine …

We describe the multi-GPU gradient boosting algorithm implemented in the XGBoost library
(https://github. com/dmlc/xgboost). Our algorithm allows fast, scalable training on multi-GPU …

We address the problem of finding influential training samples for a particular case of tree
ensemble-based models, eg, Random Forest (RF) or Gradient Boosted Decision Trees …

Food adulteration imposes a significant health concern on the community. Being one of the
key ingredients used for spicing up food dishes. Red chilli powder is almost used in every …