Software Alternatives & Reviews

LIONoso VS WEKA

Compare LIONoso VS WEKA and see what are their differences

LIONoso logo LIONoso

LIONoso is a comprehensive Machine Learning and Intelligent Optimization tool for non-profit research and academic use.

WEKA logo WEKA

WEKA is a set of powerful data mining tools that run on Java.
  • LIONoso Landing page
    Landing page //
    2021-10-09
  • WEKA Landing page
    Landing page //
    2018-09-29

LIONoso videos

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WEKA videos

Review of Feature Selection in Weka

More videos:

  • Review - Getting Started with Weka - Machine Learning Recipes #10
  • Tutorial - Data mining with Weka | Data mining Tutorial for Beginners

Category Popularity

0-100% (relative to LIONoso and WEKA)
Data Science And Machine Learning
Data Science Tools
4 4%
96% 96
Python Tools
4 4%
96% 96
Software Libraries
100 100%
0% 0

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Reviews

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WEKA Reviews

15 data science tools to consider using in 2021
Weka is free software licensed under the GNU General Public License. It was developed at the University of Waikato in New Zealand starting in 1992; an initial version was rewritten in Java to create the current workbench, which was first released in 1999. Weka stands for the Waikato Environment for Knowledge Analysis and is also the name of a flightless bird native to New...

What are some alternatives?

When comparing LIONoso and WEKA, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

NumPy - NumPy is the fundamental package for scientific computing with Python

OpenCV - OpenCV is the world's biggest computer vision library

Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

Exploratory - Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.