Results 211 to 220 of about 16,703 (255)
Some of the next articles are maybe not open access.
Leveraging LightGBM for Categorical Big Data
2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService), 2021LightGBM is a popular Gradient Boosted Decision Tree implementation for classification and regression tasks. Our contribution is to answer a research question regarding LightGBM. We would like to know which alternative yields better performance for classifying highly imbalanced Big Data with high-cardinality categorical features: relying entirely on ...
John T. Hancock, Taghi M. Khoshgoftaar
openaire +1 more source
Diagnosis of Diabetes Mellitus Using Gradient Boosting Machine (LightGBM)
Diagnostics, 2021 Diabetes mellitus (DM) is a severe chronic disease that affects human health and has a high prevalence worldwide. Research has shown that half of the diabetic people throughout the world are unaware that they have DM and its complications are increasing,
Derara Duba Rufo +2 more
exaly +2 more sources
Sales Forecasting Based on LightGBM
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2021The combination of data science and machine learning is making sales forecasting possible. This will help improve the competitiveness of retail companies. This paper is based on the LightGBM framework, which is an improved GBDT model to realize Wal-Mart sales fore-casting.
Tingyan Deng +3 more
openaire +1 more source
Model Fusion of LightGBM and SAKT for Knowledge Tracking
ACM Turing Award Celebration Conference - China ( ACM TURC 2021), 2021Knowledge tracking is to model the student’s learning interaction records so that we can evaluate the student’s learning state with relative accuracy and can adjust the students’ learning schedule appropriately or formulate a more reasonable learning plan. However, this task is very challenging. The challenges are mainly in two aspects. On the one hand,
Xin Zhou, Liming Zhang, Fanqi Meng
openaire +1 more source
An Efficient Intrusion Detection Method Based on LightGBM and Autoencoder
Symmetry, 2020 Due to the insidious characteristics of network intrusion behaviors, developing an efficient intrusion detection system is still a big challenge, especially in the era of big data where the number of traffic and the dimension of each traffic feature are ...
Nurbol Luktarhan
exaly +2 more sources
Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics, 2017
miRNAs are small noncoding RNA molecules, mainly responsible for post-transcriptional control of gene expressions. Machine learning is becoming more and more widely used in breast tumor classification and diagnosis. In this paper, we compared the performance of different machine learning methods, such as Random Forest (RF), eXtreme Gradient Boosting ...
Dehua Wang, Yang Zhang 0057, Yi Zhao
openaire +1 more source
miRNAs are small noncoding RNA molecules, mainly responsible for post-transcriptional control of gene expressions. Machine learning is becoming more and more widely used in breast tumor classification and diagnosis. In this paper, we compared the performance of different machine learning methods, such as Random Forest (RF), eXtreme Gradient Boosting ...
Dehua Wang, Yang Zhang 0057, Yi Zhao
openaire +1 more source
LightGBM Algorithm for Malware Detection
2020In Zero-Day malware challenges, attackers take advantage of every second that the anti-malware vendor delays identifying the attacking malware signature and provide the updates. Furthermore, the longer the detection phase delayed, the greater the damage to the host device.
Mouhammd Al-Kasassbeh 0001 +2 more
openaire +1 more source
Enhancing LightGBM for Industrial Fault Warning: An Innovative Hybrid Algorithm
ProcessesThe reliable operation of industrial equipment is imperative for ensuring both safety and enhanced production efficiency. Machine learning technology, particularly the Light Gradient Boosting Machine (LightGBM), has emerged as a valuable tool for ...
Azadeh Dogani
exaly +2 more sources
Gradient Boosting with XGBoost and LightGBM
2021In this chapter, you will discover the gradient boosting model. In the previous chapter, you discovered the idea behind ensemble methods. As a recap, ensemble methods make powerful predictions by combining predictions of numerous small, less performant models.
openaire +1 more source
Prediction of Gestational Diabetes Based on LightGBM
Proceedings of the 2020 Conference on Artificial Intelligence and Healthcare, 2020Gestational diabetes mellitus (GDM) is associated with an increased risk of both short-term and long-term complications in mothers and infants. However, if lifestyle interventions are initiated at or before the 15th week of pregnancy, the risk of GDM could be reduced by 20% during pregnancy.
Fan Hou +3 more
openaire +1 more source