tulasinnd/Industrial-Copper-Modeling-Project
The copper industry faces challenges in predicting selling prices and lead classification. However, by utilizing advanced techniques such as data normalization, outlier detection and handling, and using tree-based models such as the decision tree algorithm, we can provide accurate predictions and optimize pricing decisions and leads classification
This project helps professionals in the copper industry accurately predict selling prices and classify sales leads. You input various sales and pricing data points, and the system outputs either a predicted selling price or a classification of whether a lead is 'WON' or 'LOST'. This is designed for sales managers, pricing analysts, and business development teams in the copper sector.
No commits in the last 6 months.
Use this if you need to quickly and accurately forecast copper selling prices or determine the likelihood of a sales lead converting.
Not ideal if your industry is outside of copper or your prediction needs extend beyond pricing and lead classification.
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Last pushed
Apr 30, 2023
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