CUSTOMER CHURN PREDICTION
A machine learning program that predicts customer churn (yes(1) or no(0)) from a telecos data company.This program uses extreme gradient boosting technique in predicting outcomes.
Data set and its description
| Data | Description |
|---|---|
| Customer ID | Customer unique identifier |
| Gender | Whether the customer is a male or a female |
| Senior Citizen | Whether the customer is a senior citizen or not (1, 0) |
| Partner | Whether the customer has a partner or not (Yes, No) |
| Dependents | Whether the customer has dependents or not (Yes, No) |
| Tenure | Number of months the customer has stayed with the company |
| Phone service | Whether the customer has a phone service or not (Yes, No) |
| Multiple lines | Whether the customer has multiple lines or not (Yes, No, No phone service) |
| Internet Service | Customer’s internet service provider (DSL, Fiber optic, No) |
| Online security | Whether the customer has online security or not (Yes, No, No internet service) |
Dependecies and packgages
*numpy>=1.20.0,<1.21.0 *xgboost *pandas>=1.3.5,<1.4.0 *pydantic>=1.8.1,<1.9.0 *scikit-learn>=1.0.2,<1.1.0 *strictyaml>=1.3.2,<1.4.0 *ruamel.yaml==0.16.12 *feature-engine>=1.0.2,<1.1.0 *joblib>=1.0.1,<1.1.0
Source code link
Source code link: Github link
1 maintainer
Release files for customer-churn-classification-model 3.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| customer-churn-classification-model-3.0.3.tar.gz | 194.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| customer_churn_classification_model-3.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 401.9 kB
Release files / customer-churn-classification-model-3.0.3.tar.gz
| Download URL | customer-churn-classification-model-3.0.3.tar.gz |
|---|---|
| Size | 194.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d80307d5e5ce76105ac603c52f06744839255144297f06f1d1472645bcdbc149
|
|
BLAKE2b-256 checksum How to use checksums |
af11378f9839b106c38ca57ac607d55352ba6f2562f21c5b3db319c7ea049a82
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.12
|
Release files / customer_churn_classification_model-3.0.3-py3-none-any.whl
| Download URL | customer_churn_classification_model-3.0.3-py3-none-any.whl |
|---|---|
| Size | 207.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e76934beabc6b4f7f173af64b45f6bea7fca33616d7cf0433e5c17e92183d334
|
|
BLAKE2b-256 checksum How to use checksums |
c7e0d7aed147db5a0343f9523c5d6bb810410ab7b9b466e7248b9fd5399ed239
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.12
|
