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Predictive analysis of the classical 'Sales Win/Loss' dataset

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Sales-Win-Loss-prediction

Predictive analysis of the classical 'Sales Win/Loss' dataset

The following models have been used in this prediction :

  1. Gaussian Naive Bayes
  2. Linear Support Vectors Classification
  3. K Neighbors Classifier

The Sales-Win-Loss dataset was cloned from

https://github.com/vkrit/data-science-class/blob/master/WA_Fn-UseC_-Sales-Win-Loss.csv

Here's a sample of dataset used :

Data sample

Using this data,it's predicted if a new sale will be a win or a loss.

References to the working of above used algorithms are given below :

  1. Gaussian Naive Bayes :

    https://scikit-learn.org/stable/modules/naive_bayes.html#gaussian-naive-bayes

  2. Linear SVC :

    https://scikit-learn.org/stable/modules/svm.html

  3. K-Neighbors Classifier :

    https://scikit-learn.org/stable/modules/neighbors.html

Prediction idea : Dataquest.io , Linkedin.com

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Predictive analysis of the classical 'Sales Win/Loss' dataset

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