Results 11 to 20 of about 7,680 (217)

CatBoostLSS -- An extension of CatBoost to probabilistic forecasting

CoRR, 2020
We propose a new framework of CatBoost that predicts the entire conditional distribution of a univariate response variable. In particular, CatBoostLSS models all moments of a parametric distribution (i.e., mean, location, scale and shape [LSS]) instead of the conditional mean only.
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CatBoost-Based Automatic Classification Study of River Network

ISPRS International Journal of Geo-Information, 2023
Existing research on automatic river network classification methods has difficulty scientifically quantifying and determining feature threshold settings and evaluating weights when calculating multi-indicator features of the local and overall structures of river reaches.
Di Wang, Haizhong Qian
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Introducing a Novel Method for Determining the Future Price of the Financial Markets: A Case Study of the Hang Seng Index [PDF]

Journal of Artificial Intelligence and System Modelling
The stock market is highly complex, with numerous unpredictable factors influencing stock prices. The relationship between supply and demand, alongside external events, makes it difficult to forecast future market behavior with high accuracy. While stock
Afreen Akashi, Md Sanadiule Ullash, Apurba Das   +2 more
doaj   +1 more source

Sand Cat Swarm Optimizer with CatBoost for Sarcoidosis Diagnosis

2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI), 2023
In the last few years, machine learning has increased in popularity across many disciplines. This paper aims to comprehensively analyze the CatBoost classification algorithm in the context of Sarcoidosis. Analysis was undertaken to evaluate the performance of the CatBoost classification algorithm in comparison to other classifiers.
Youssef, Merna, Sharfo, Samer M., Attar, Hani, Deif, Mohanad A., Hafez, Mohamed, Solyman, Ahmad   +5 more
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A Comparative Study of CatBoost and Double Random Forest for Multi-class Classification

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2023
Multi-class classification has its challenge compared to binary classification. The challenges mainly caused by the interactions between explanatory and responses variable are increasingly complex.
Annisarahmi Nur Aini Aldania, Agus Mohamad Soleh, Khairil Anwar Notodiputro   +2 more
doaj   +1 more source

CatBoost: gradient boosting with categorical features support

CoRR, 2018
In this paper we present CatBoost, a new open-sourced gradient boosting library that successfully handles categorical features and outperforms existing publicly available implementations of gradient boosting in terms of quality on a set of popular publicly available datasets.
Anna Veronika Dorogush, Vasily Ershov, Andrey Gulin   +2 more
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Research on a short-term photovoltaic power prediction method based on CatBoost

Zhejiang dianli, 2023
The intermittent and fluctuating generation power of PV power plants has an increasingly prominent impact on the safe， stable， and economical operation of power grids.
CHEN Haihong, YI Yongli, HUANG Shen, HAN Jingyi   +3 more
doaj   +1 more source

CatBoost: unbiased boosting with categorical features

, 2017
This paper presents the key algorithmic techniques behind CatBoost, a new gradient boosting toolkit. Their combination leads to CatBoost outperforming other publicly available boosting implementations in terms of quality on a variety of datasets. Two critical algorithmic advances introduced in CatBoost are the implementation of ordered boosting, a ...
Liudmila Ostroumova Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin   +4 more
openaire   +3 more sources

Discharge estimation in compound channels with converging and diverging floodplains using an optimised Gradient Boosting Algorithm

Journal of Hydroinformatics
River discharge estimation is vital for effective flood management and infrastructure planning. River systems consist of a main channel and floodplains, collectively forming a compound channel, posing challenges in discharge calculation, particularly ...
Shashank Shekhar Sandilya, Bhabani Shankar Das, Sébastien Proust, Divyanshu Shekhar   +3 more
doaj   +1 more source

Predictive Model for Reducing Employee Turnover Using Machine Learning Techniques

Journal of Human Resource Management
Purpose - The problem of employee turnover is a chronic disruption in the stability of organizations, them functioning, and their long-term development.
Khadiga ABDELKARIM, Mahgoub ABDELRAHIM, Baraa ELTAYEB   +2 more
doaj   +1 more source