https://github.com/halacoded/riskintel
machine learning model (RandomForestClassifier) that predicts whether a customer is "risky" or "not risky" based on various features
https://github.com/halacoded/riskintel
classification coded kuwait machine-learning random-forest-classifier randomforestclassifier
Last synced: 4 months ago
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machine learning model (RandomForestClassifier) that predicts whether a customer is "risky" or "not risky" based on various features
- Host: GitHub
- URL: https://github.com/halacoded/riskintel
- Owner: halacoded
- Created: 2025-06-04T17:05:07.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-06-04T17:16:00.000Z (5 months ago)
- Last Synced: 2025-06-04T22:38:13.623Z (5 months ago)
- Topics: classification, coded, kuwait, machine-learning, random-forest-classifier, randomforestclassifier
- Homepage: https://colab.research.google.com/drive/1jgdWd_1ry3z4Xxnh68Tm41Ca-xdHP4-n?usp=sharing
- Size: 442 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# RiskIntel: Customer Risk Classification
## Overview
RiskIntel is a machine learning project designed to predict whether a customer is "risky" or "not risky" based on various features. This model helps businesses assess customer risk and make informed decisions.
## Dataset
The dataset used for training is **Customer_Risky_Not_Risky.csv**, which contains the following columns:
- **label**: Target variable (1 for risky, 0 for not risky)
- **id**: Unique identifier for each customer
- **fea_1 to fea_11**: Various features influencing risk assessment
## Objectives
- Develop a predictive model to classify customer risk.
- Utilize feature engineering and machine learning techniques.
- Evaluate the model's performance using accuracy, precision, recall, and F1-score.
## Installation & Usage
### Prerequisites
- Python 3.x
- COLAP
- Required libraries: pandas, numpy, scikit-learn RandomForestClassifier , matplotlib.pyplot , seaborn
### Setup
Click COLAP Link And Downalod Dataset then You are Ready to start