SVM Classifier for Customer Purchase Prediction in Python

This is basically a classifier that takes certain parameters as input and then gives the output whether the customer is likely to buy a product or not made in Python.

This project is built on the SVM Classifier model that takes names(not used in training/used for output recognition purpose), age, monthly salary and whether the person is likely to buy a product(1) or not(0) as the training set and then tarins the model. The testing set verifies the accuracy of the model. The program also uses libraries like matplotlib for visualization purposes and can be used for a better understanding of the model.

This packet uses fewer parameters and is built as a prototype. It can be modified to be used in various marketing or sales segments of a company by inserting other parameters into the training set as per the requirement of the company. The packet contains code at the end which takes user input which is not directly beneficial if you are running the program only. It can be useful when implemented as different source code for predicting in a live customer interaction which somehow predicts the likelihood of a purchase by the same customer.

How to use: Run the program all at once. You'll be prompted to give inputs in the Python console. Once you give inputs, the model will give output according to the dataset I've used. In case you need a different dataset, you can import a different one but in the same format as I've used. Since this program uses print statements to give output in the Python Console, you can not print it and integrate with with python programs.

Coders Packet

SVM Classifier for Customer Purchase Prediction in Python

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