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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

Documentation | Wiki | Mailing list | Stack Overflow | FAQ | IRC

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
Orange   Torch   Apache Mahout   Apache MXNet (Incubating)   Apache Spark   Apache SystemML   Eclipse Deeplearning4j   MALLET   Massive Online Analysis (MOA)   mlpack   OpenCV   TensorFlow   The Microsoft Cognitive Toolkit   Weka   Yooreeka   PyTorch  
Data Mining
Orange   ELKI   Massive Online Analysis (MOA)   OpenNN   Weka   Yooreeka  
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: Fixed syntax in software source files (1e763e9)