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

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Experimental

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.

copper-industry sales-forecasting lead-scoring pricing-strategy business-development
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 14 / 25

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Last pushed

Apr 30, 2023

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