Data mining toolbox in python

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Název: Data mining toolbox in python
Autoři: Tomaz ̌ Curk, Ales ̌ Erjavec, Matija Polajnar, Marko Toplak, Lan Umek, Blaz ̌ Zupan
Přispěvatelé: The Pennsylvania State University CiteSeerX Archives
Zdroj: http://jmlr.csail.mit.edu/papers/volume14/demsar13a/demsar13a.pdf.
Rok vydání: 2013
Sbírka: CiteSeerX
Témata: Python, data mining, machine learning, toolbox, scripting
Popis: Orange is a machine learning and data mining suite for data analysis through Python scripting and visual programming. Here we report on the scripting part, which features interactive data analysis and component-based assembly of data mining procedures. In the selection and design of components, we focus on the flexibility of their reuse: our principal intention is to let the user write simple and clear scripts in Python, which build upon C++ implementations of computationally-intensive tasks. Orange is intended both for experienced users and programmers, as well as for students of data mining.
Druh dokumentu: text
Popis souboru: application/pdf
Jazyk: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.674.2849; http://jmlr.csail.mit.edu/papers/volume14/demsar13a/demsar13a.pdf
Dostupnost: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.674.2849
http://jmlr.csail.mit.edu/papers/volume14/demsar13a/demsar13a.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Přístupové číslo: edsbas.8EB7796A
Databáze: BASE
Popis
Abstrakt:Orange is a machine learning and data mining suite for data analysis through Python scripting and visual programming. Here we report on the scripting part, which features interactive data analysis and component-based assembly of data mining procedures. In the selection and design of components, we focus on the flexibility of their reuse: our principal intention is to let the user write simple and clear scripts in Python, which build upon C++ implementations of computationally-intensive tasks. Orange is intended both for experienced users and programmers, as well as for students of data mining.