Results 231 to 240 of about 505,761 (263)

Improving SVM Classification with Imbalance Data Set

2009
In view of inconsistent problems caused by that Synthetic Minority Over-sampling Technique (SMOTE) and Support Vector Machine (SVM) work in different space, this paper presents a kernel-based SMOTE approach to solve classification with imbalance data set by SVM.
Zhi-Qiang Zeng, Ji Gao
openaire   +1 more source

Data Imbalance Problem in Text Classification

2010 Third International Symposium on Information Processing, 2010
Aimming at the ever-present problem of imbalanced data in text classification, the authors study on several forms of imbalanced data, such as text number, class size, subclass and class fold. Some useful conclusions are gotten from a series of correlative experiments: first, when the text of two class is almost the same number, the difference of word ...
Yanling Li, Guoshe Sun, Yehang Zhu
openaire   +1 more source

An Experimental Analysis to Learn Data Imbalance in Scholarly Data

2021
Data imbalance is a key challenge in the majority of real-world classification problems. It refers to the disparity of data instances corresponding to either of the class labels. Data imbalance is studied in detail with respect to many data domains such as transaction data, medical data, e-commerce data, meteorological data, social media data, and web ...
Mitali Desai, Rupa G. Mehta, Dipti P. Rana   +2 more
openaire   +1 more source

EasyEnsemble and Feature Selection for Imbalance Data Sets

2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, 2009
There are many labeled data sets which have an unbalancedrepresentation among the classes in them. When the imbalance islarge, classification accuracy on the smaller class tends to belower. In particular, when a class is of great interest but occursrelatively rarely such as cases of fraud, instances of disease, andso on, it is important to accurately ...
openaire   +1 more source

The Influence of Data Imbalance on Feature Selection

Advanced Materials Research, 2012
Data imbalance problem is urgent problem in data mining and machine learning fields, the standard classifier will tend to over-adapt to the large categories and ignore the small categories. According to this problem, this paper takes two categories of text classification problem as the background, respectively from the amount of text and the text ...
Yan Ling Li, Kui Xia Han, Ye Hang Zhu
openaire   +1 more source

PoiseNet: Dealing With Data Imbalance in DensePose

IEEE Transactions on Circuits and Systems for Video Technology, 2023
Junyao Sun, Jingkai Zhou, Qiong Liu 0006
openaire   +1 more source

DATA IMBALANCE IN MULTILABEL CLASSIFICATION

2023
Adhithya Sudeesh, Nair, Pramod
openaire   +1 more source

Imbalance Problems in Object Detection: A Review

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Kemal Oksuz, Baris Can Cam, Sinan Kalkan   +2 more
exaly  

Effective Imbalance Learning Utilizing Informative Data

2022
Han Tai, Raymond K. Wong 0001, Bing Li 0010   +2 more
openaire   +1 more source

Does fiscal decentralization improve energy and environmental performance? New perspective on vertical fiscal imbalance

Applied Energy, 2021
Boqiang Lin, Yicheng Zhou
exaly