A Survey on Open Source Data Mining Tools for SMEs

2016 ◽  
pp. 253-262 ◽  
Author(s):  
Pedro Almeida ◽  
Jorge Bernardino
Keyword(s):  
Data Mining ◽  
Open Source ◽  
Open Source Data ◽  
Source Data ◽  
Mining Tools

scholarly journals Open Source Data Mining Tools Evaluation using OSSpal Methodology

2018 ◽  
Author(s):  
Any Keila Pereira ◽  
Ana Paula Sousa ◽  
João Ramalho Santos ◽  
Jorge Bernardino
Keyword(s):  
Data Mining ◽  
Open Source ◽  
Open Source Data ◽  
Source Data ◽  
Mining Tools

Open Source Data Mining Tools for Sports

2010 ◽  
pp. 89-92 ◽  
Author(s):  
Robert P. Schumaker ◽  
Osama K. Solieman ◽  
Hsinchun Chen
Keyword(s):  
Data Mining ◽  
Open Source ◽  
Open Source Data ◽  
Source Data ◽  
Mining Tools

scholarly journals A Comprehensive Analysis of Proprietary and Open Source Data Mining Tools

2020 ◽  
pp. 414-420
Author(s):  
Sonia Rani Chowdhary ◽  
Mr Vikash
Keyword(s):  
Data Mining ◽  
Open Source ◽  
Rapid Development ◽  
Time Analysis ◽  
Open Source Data ◽  
Source Data ◽  
Efficient Information ◽  
Tools And Techniques ◽  
Short Time ◽  
Mining Tools

The Powerful software tools and techniques required for the development of data mining applications. With the rapid development of technologies and business interest in using electronics and latest technologies plays important role in improvement of data mining field. Data mining access the meaningful and efficient information available in worldwide which is helps in decision making. This paper described the (a) various tools and techniques used by data mining applications. (b) compared features and limitations both in Proprietary and open sources data mining tools. (c) technical analysis of proprietary and open source data mining tools. On the basis of well-designed User interface, short time analysis, statistical and mathematical analysis user can select the best tool as per their requirements. Analysis of these tools makes easy to select appropriate tool.

A Comparison of Open Source Data Mining Tools for Breast Cancer Classification

2017 ◽  
pp. 636-651 ◽  
Author(s):  
Ahmed AbdElhafeez Ibrahim ◽  
Atallah Ibrahin Hashad ◽  
Negm Eldin Mohamed Shawky
Keyword(s):  
Breast Cancer ◽  
Data Mining ◽  
Open Source ◽  
Experimental Results ◽  
Classification Task ◽  
Open Source Data ◽  
Source Data ◽  
Precise Tool ◽  
Feature Values ◽  
Mining Tools

Data Mining is a field that interconnects areas from computer science, trying to discover knowledge from databases in order to simplify the decision making. Classification is a Data Mining chore that learns from a set of instances in order to precisely classify the target class for new instances. Open source Data Mining tools can be used to make classification. This paper compares four tools: KNIME, Orange, Tanagra and Weka. Our goal is to discover the most precise tool and technique for breast cancer classifications. The experimental results show that some tools achieve better results more than others. Also, using fusion classification task verified to be better than the single classification task over the four datasets have been used. Also, we present a comparison between using complete datasets by substituting missing feature values and incomplete ones. The experimental results show that some datasets have better accuracy when using complete datasets.

Open Source Data Mining Tools Evaluation using OSSpal Methodology

2018 ◽  
Author(s):  
Any Keila Pereira ◽  
Ana Paula Sousa ◽  
João Ramalho Santos ◽  
Jorge Bernardino
Keyword(s):  
Data Mining ◽  
Open Source ◽  
Open Source Data ◽  
Source Data ◽  
Mining Tools
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