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Created 2 years ago
Background
- Operators are losing in today’s competitive market. Churn is a key driver and is an industry wide challenge. A churned customer provides less revenue or zero revenue and increases competitor market share. Increase acquisition cost for the service provide if the customer churned to competition. It costs up to 5 times as much for a Service provider to acquire a new subscriber as to retaining an existing one.
Goal
- This analysis will asses the classification of subscribers, asses insights on churn behavior of subscribers and using the information to strategize new marketing initiatives.
Dataset info
- Sample Dataset containing Telco customer data and showing Customers that left last month
Methodology
- Install and load Python libraries
- Explore the data
- Train Test Split
- Decision Tree Classifier
- Random Forest Classifier
- Performing PCA
- Pickling the model and Deployment
Tools
-Python, Jupyter notebooks
Install and load Python libraries
import pandas as pd
from sklearn import metrics
from sklearn.model_selection import train_test_split
from sklearn.metrics import recall_score
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.tree import DecisionTreeClassifier
from imblearn.combine import SMOTEENN
Reading csv and Explore the data
df=pd.read_csv("tel_churn.csv")
df.head()