How to address the data quality issues in regression models: A guided process for data cleaning
Today, data availability has gone from scarce to superabundant. Technologies like IoT,
trends in social media and the capabilities of smart-phones are producing and digitizing lots …
trends in social media and the capabilities of smart-phones are producing and digitizing lots …
A case-based reasoning system for recommendation of data cleaning algorithms in classification and regression tasks
Abstract Recently, advances in Information Technologies (social networks, mobile
applications, Internet of Things, etc.) generate a deluge of digital data; but to convert these …
applications, Internet of Things, etc.) generate a deluge of digital data; but to convert these …
Consumption behavior analysis of over the top services: Incremental learning or traditional methods?
JS Rojas, A Rendon, JC Corrales - IEEE Access, 2019 - ieeexplore.ieee.org
Network monitoring and analysis of consumption behavior are important aspects for network
operators. The information obtained about consumption trends allows to offer new data …
operators. The information obtained about consumption trends allows to offer new data …
[HTML][HTML] A systematic review of data quality issues in knowledge discovery tasks
ABSTRACT arge volume of data is growing because the organizations are continuously
capturing the collective amount of data for better decision-making process. The most …
capturing the collective amount of data for better decision-making process. The most …
From theory to practice: A data quality framework for classification tasks
The data preprocessing is an essential step in knowledge discovery projects. The experts
affirm that preprocessing tasks take between 50% to 70% of the total time of the knowledge …
affirm that preprocessing tasks take between 50% to 70% of the total time of the knowledge …
Development of a Framework to Aid the Transition from Reactive to Proactive Maintenance Approaches to Enable Energy Reduction
M Ahern, DTJ O'Sullivan, K Bruton - Applied Sciences, 2022 - mdpi.com
The disparity between public datasets and real industrial datasets is limiting the practical
application of advanced data analysis. Therefore, industry is stuck in a reactive mode …
application of advanced data analysis. Therefore, industry is stuck in a reactive mode …
Feature selection for classification tasks: Expert knowledge or traditional methods?
Recently, available data has increased explosively in both number of samples and
dimensionality. The huge number of high dimensional data generates the presence of noisy …
dimensionality. The huge number of high dimensional data generates the presence of noisy …
Characterization of usage data with the help of data classifications
Comprehensive data understanding is a key success driver for data analytics projects.
Knowing the characteristics of the data helps a lot in selecting the appropriate data analysis …
Knowing the characteristics of the data helps a lot in selecting the appropriate data analysis …
Two-level classifier ensembles for coffee rust estimation in Colombian crops
Rust is a disease that leads to considerable losses in the worldwide coffee industry. There
are many contributing factors to the onset of coffee rust eg Crop management decisions and …
are many contributing factors to the onset of coffee rust eg Crop management decisions and …
Estimation of coffee rust infection and growth through two-level classifier ensembles based on expert knowledge
Rust is a disease that leads to considerable losses in the worldwide coffee industry. There
are many contributing factors to the onset of coffee rust, eg, crop management decisions and …
are many contributing factors to the onset of coffee rust, eg, crop management decisions and …