Herrera, "A survey on data preprocessing for data stream min- ing: Current status and future directions," Neurocomputing, vol. 239, pp. 39-57, May 2017.Sergio R., Bartosz K., Salvador G., Michał W. ,and Francisco H.: A survey on data prepro- cessing for data stream mining: ...
Batteries are of paramount importance for the energy storage, consumption, and transportation in the current and future society. Recently machine learning (ML) has demonstrated success for improving lithium-ion technologies and beyond. This in-depth review aims to provide state-of-art achievements in...
Data mining and Big Data analytics are helping to realize the goals of diagnosing, treating, helping, and healing all patients in need of healthcare, with the end goal of this domain being improved Health Care Output (HCO), or the quality of care that healthcare can provide to end users ...
1.1. Data mining Data mining (DM) has grown from a promising technology to an established powerful and effective analytical tool to interpret massive and complex data. In 2001, MIT reviewed DM as one of the top 10 emerging technologies that will change the world [3], while it has now accu...
Enterprises, as key emitters, play a vital role in promoting sustainable development. Corporate sustainability disclosure provides a key channel for stakeholders to gain insights into a company’s sustainability progress. However, few studies have been c
First, raw wind data properties are analyzed, and all the data are divided into six categories according to their attribute magnitudes from a statistical perspective. Next, the weighted distance, a novel concept of the degree of similarity between the individual objects in the wind database and ...
APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA A dataset of 2398 records with 63 attributes were used for clustering purpose. Apriori is an association rule algorithm which is implemented in Weka soft...
of these overfitting solutions is provided below. A complete survey of regularization methods in Deep Learning has been compiled by Kukacka et al. [6]. Knowledge of these overfitting solutions will inform readers about other existing tools, thus framing the high-level context of Data Augmentation ...
The presence of missing values in real-world data is not only a prevalent problem but also an inevitable one. Therefore, missing values should be handled carefully before the mining or learning process. This paper proposes a novel technique to impute missing data. It employs a new version of ...
In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques ...