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The prediction was done to examine the relationship between various prices in order to maximize profit. While the classification was done using random forest classification to classify the most important features in terms of percentage and also to check the days for most products to be manufactured.

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Name		Name	Last commit message	Last commit date
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CLASSIFICATION.ipynb		CLASSIFICATION.ipynb
LICENSE		LICENSE
PREDICTION .ipynb		PREDICTION .ipynb
Products_Filtered.csv		Products_Filtered.csv
README.md		README.md

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Classification-and-Prediction

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The prediction was done to examine the relationship between various prices in order to maximize profit. While the classification was done using random forest classification to classify the most important features in terms of percentage and also to check the days for most products to be manufactured.

python linear-regression jupyter-notebook prediction km classification scatter-plot random-forest-classifier

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