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scikit-learn

scikit-learn is a machine learning library for the Python programming language

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Overview

scikit-learn is an open source machine learning library featuring classification, regression, clustering, dimensionality reduction, model selection and preprocessing. It has tools for data mining and data analysis, and is built on NumPy, SciPy, and matplotlib.

As per official website , it features:

  • Classification : Identifying to which category an object belongs to
  • Regression : Predicting a continuous-valued attribute associated with an object
  • Clustering : Automatic grouping of similar objects into sets
  • Dimensionality reduction : Reducing the number of random variables to consider
  • Model selection : Comparing, validating and choosing parameters and models
  • Preprocessing : Feature extraction and normalization

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Platform

   

Social

 

System Requirements

#Minimum
1Python (>= 2.7 or >= 3.4), NumPy (>= 1.8.2), SciPy (>= 0.13.3).

Ratings

Aggregate
4.70 
 5
G2CROWD4.9 
 5		based on 30 reviews
InfoWorld4.5 
 5		based on professional's opinion

Developer

David Cournapeau(OD), Contributors

Written in

Python, Cython, C, C++

Initial Release

June 2007

Repository

https://github.com/scikit-learn/scikit-learn

License

BSD-3

Categories

Machine Learning, Data Mining, Data Analysis, Framework

Alternatives

Machine Learning
Apache Mahout   Apache SystemML   Eclipse Deeplearning4j   MALLET   Massive Online Analysis (MOA)   OpenCV   TensorFlow   The Microsoft Cognitive Toolkit   Torch   Yooreeka   Orange   Apache MXNet (Incubating)   Apache Spark   mlpack   Weka   PyTorch  
Data Mining
Massive Online Analysis (MOA)   Yooreeka   Orange   ELKI   OpenNN   Weka  
Data Analysis
Orange   pandas  

Notes

  • scikit-learn 0.20 is the last version to support Python 2.7 and Python 3.4. scikit-learn 0.21 will require Python 3.5 or newer.

This page was last updated with commit: Now custom 'Remarks' are allowed instead of just 'Portable' in 'Get it'; all software's source files have been updated accordingly (0cb3959)