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Python: Data Analytics and Visualization

You're reading from   Python: Data Analytics and Visualization Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Product type Course
Published in Mar 2017
Publisher Packt
ISBN-13 9781788290098
Length 866 pages
Edition 1st Edition
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Authors (4):
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Martin Czygan Martin Czygan
Author Profile Icon Martin Czygan
Martin Czygan
Ashish Kumar Ashish Kumar
Author Profile Icon Ashish Kumar
Ashish Kumar
Kirthi Raman Kirthi Raman
Author Profile Icon Kirthi Raman
Kirthi Raman
Phuong Vo.T.H Phuong Vo.T.H
Author Profile Icon Phuong Vo.T.H
Phuong Vo.T.H
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Toc

Chapter 7. Clustering with Python

In the previous two chapters, we discussed and understood two important algorithms used in predictive analytics, namely, linear regression and logistic regression. Both of them are very widely used. They are supervised algorithms. If you stress your memory a tad bit and have thoroughly read the previous chapters of the book, you would remember that a supervised algorithm is one where the historical value of an output variable is known from the data. A supervised algorithm uses this value to train and build the model to forecast the value of an output variable for a dataset in future. An unsupervised algorithm, on the other hand, doesn't have the luxury or constraints (different perspectives of looking at it) of the output variable. It uses the values of the predictor variables instead to build a model.

Clustering—the algorithm that we are going to discuss in this chapter—is an unsupervised algorithm. Clustering or segmentation...

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Python: Data Analytics and Visualization
Published in: Mar 2017
Publisher: Packt
ISBN-13: 9781788290098
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