Weka3.8.2

Weka Development Team(Open Source)

Punteggio utente7

Pubblicità

Weka is a collection of machine learning algorithms for solving real-world data mining issues. The algorithms can either be applied directly to a data set or called from your own Java code.

The application contains the tools you'll need for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also appropriate for developing new machine learning schemes.

Key features include:

  • Machine learning.
  • Data mining.
  • Pre-processing.
  • Classification.
  • Regression.
  • Clustering.
  • Association rules.
  • Attribute selection.
  • Experiments.
  • Workflow.
  • Visualization.

Weka's collection of algorithms range from those that handle data pre-processing to modeling. It's core data mining algorithms include regression, clustering and classification.

Although Weka has a full suite of algorithms for data analysis, it has been built to handle data as single flat files. Subsequently, it does not handle multi-relational mining and sequence modeling.

Overall, Weka is a good data mining tool with a comprehensive suite of algorithms. The interface is OK, although with four to choose from, each with their own strengths, it can be awkward to choose which to work with, unless you have a thorough knowledge of the application to begin with.

Looking for the Mac version of Weka? Download Here

Titolo:
Weka,3.8.2 per Windows
Dimensione File:
50.82 MB
Requisiti:
  • Windows 10,
  • Windows 7 64-Bit,
  • Windows Vista 64-bit,
  • Windows 10 64-bit,
  • Windows 2008 R2,
  • Windows 2008 64-bit,
  • Windows Vista,
  • Windows 2003,
  • Windows 7,
  • Windows 2000,
  • Windows 9x,
  • Windows 8,
  • Windows XP,
  • Windows 2012,
  • Windows 2008,
  • Windows XP 64-bit,
  • Windows 8 64-bit
Lingua:
Italiano
Lingue disponibili:
  • Italiano,
  • Inglese,
  • Francese,
  • Spagnolo,
  • Polacco,
  • Cinese,
  • Tedesco,
  • Giapponese
Licenza:
Open Source
Data Aggiunta
Monday, January 15th 2018
Autore:
Weka Development Team

https://www.cs.waikato.ac.nz/ml/weka

SHA-1:
9ffa8e4f1765134c50334c0cc6a9ea743b1bf359

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