SciKit-Learn : The robust library for machine learning in Python

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SciKit-Learn : The robust library for machine learning in Python

Scikit-learn (Sklearn) provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction via a consistent interface in Python.

 

Prerequisites for Scikit-learn

Before we start using scikit-learn latest release, we require the following:

  • Python (>=3.5)
  • NumPy (>= 1.11.0)
  • Scipy (>= 0.17.0)
  • Joblib (>= 0.11)
  • Matplotlib (>= 1.5.1) is required for Sklearn plotting capabilities.
  • Pandas (>= 0.18.0) is required for some of the scikit-learn examples using data structure and analysis.

 

SciKit-Learn Features

Rather than focusing on loading, manipulating, and summarising data, Scikit-learn library is focused on modeling the data. Some of the most popular groups of models provided by Sklearn are as follows:

Supervised Learning algorithms: Almost all the popular supervised learning algorithms, like Linear Regression, Support Vector Machine (SVM), Decision Tree (can see in continues), etc., are part of scikit-learn.

Unsupervised Learning algorithms: On the other hand, it also has all the popular unsupervised learning algorithms from clustering, factor analysis, PCA (Principal Component Analysis) to unsupervised neural networks.

Clustering: This model is used for grouping unlabeled data.

Cross-Validation: It is used to check the accuracy of supervised models on unseen data.

Dimensionality Reduction: It is used for reducing the number of attributes in data which can be further used for summarization, visualization, and feature selection.

Ensemble methods: As the name suggests, it is used for combining the predictions of multiple supervised models.

Feature extraction: It is used to extract the features from data to define the attributes in image and text data.

Feature selection: It is used to identify useful attributes to create supervised models.

Open Source: It is an open-source library and also commercially usable under a BSD license.

 

Decision Trees (DTs) by SciKit-Learn in Python

 

 

 

 

References:

  1. www.tutorialspoint.com
  2. www.scikit-learn.org

 

By |2020-11-29T12:35:36+03:3020th November, 2020|Categories: DS knowledge, Python knowledge|Tags: , , |0 Comments

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