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Use of Data Mining for Intelligent Evaluation of Imputation Methods
In real-world situations, researchers frequently face the difficulty of missing values (MV), i.e., values not observed in a data set. Data imputation techniques allow the estimation of MV using different algorithms, by ...
Descontinuidade de empresas brasileiras do setor de consumo não cíclico: um estudo com dados contábeis utilizando técnicas de data miningDiscontinuance of Brazilian companies from non-cyclic consumer goods industry: a study with financial data using data mining techniques
(Universidade Federal de Pernambuco, 2019)
Visualizing the document pre-processing effects in text mining process
(2018-01-01)
Text mining is an important step to categorize textual data by using data mining techniques. As most obtained textual data is unstructured, it needs to be processed before applying mining algorithms – that process is known ...
Revisão de métodos para análise de agrupamento de dados em data mining
(Universidade Tecnológica Federal do ParanáPato BrancoBrasilBanco de Dados: Administração e DesenvolvimentoUTFPR, 2017-02-23)
The core components of data mining technology have been in development for decades. Today, the maturity of these techniques, coupled with high-performance database engines and extensive data integration efforts, make these ...
Statistical Comparisons of the Top 10 Algorithms in Data Mining for Classification Task
This work is builds on the study of the 10 top data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) community in December 2006. We address the same study, but with the application ...
Comparison of the techniques decision tree and MLP for data mining in SPAMs detection to computer networks
(2013-12-31)
Anomalies in computer networks has increased in the last decades and raised concern to create techniques to identify these unusual traffic patterns. This research aims to use data mining techniques in order to correctly ...
Reducing the Number of Canonical Form Tests for Frequent Subgraph Mining
(Revista Computación y Sistemas; Vol. 15 No. 2, 2011-12-13)
Abstract. Frequent connected subgraph (FCS) mining is an interesting problem with wide applications in real life. Most of the FCS mining algorithms have been focused on detecting duplicate candidates using canonical form ...
Data Mining and Endocrine Diseases: A New Way to Classify?
(Elsevier, 2018-04)
Data mining consists of using large database analysis to detect patterns, relationships and
models in order to describe (or even predict) the appearance of a future event; to accomplish
this, it uses classification ...
MR-Radix: a multi-relational data mining algorithm
(2012)
Abstract
Background
Once multi-relational approach has emerged as an alternative for analyzing structured data such as ...