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Consumer complaint Analysis and prediction - A detailed case study of customer complaints in a firm and training multiple machine learning models.

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Personal-Project

Consumer complaints analysis and prediction using ML and Python. 💻🚀

A detailed case study of customer complaints in a firm and training multiple machine learning modes. The goal is to use machine learning approaches to anticipate and evaluate customer complaint data.

Goal:

Classify consumer complaints into predefined categories.

Classification algorithms:

Support Vector Machine (SVM) and Decision Tree.

About Dataset:

- Date received: Date of complaint received

- Product: Product about which complaint was registered

- Sub-product: Sub-product about which complaint was registered

- Issue: Issue about which complaint was registered - high level

- Consumer complaint narrative: Text of the complaint

- Company public response

- Company: Company Name against which complaint was registered

- State: State of the complaint

- ZIP code: Zip Code of the complaint

- Tags

- Consumer consent provided?

- Submitted via

- Date sent to the company

- Company response to consumer

- Timely response?

- Consumer disputed?

- Complaint ID

Model Accuracy: 81%

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Consumer complaint Analysis and prediction - A detailed case study of customer complaints in a firm and training multiple machine learning models.

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