Summary Statistics

Exploratory Graphics

Checking for outliers

Checking for Missing Values

Dealing with Missing Values

Eliminate or transform variables if necessary.

Application of methods (classification, association rules or clustering)

Evaluation results (accuracy, sensivity, etc.)

About dataset:

The Dataset belongs to the telecommunications company.

Response (target) variable is churn.

Each row represents a customer, each column contains customers attributes.

The Churn column is our target. Finding the model that best predicts the desired churn

(yes) situation.

Definitions of Attributes:

customerID ==> Customer ID

gender ==> Whether the customer is a male or a female

SeniorCitizen ==> 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

PhoneService ==> Whether the customer has a phone service or not (Yes, No)

MultipleLines ==> Whether the customer has multiple lines or not (Yes, No, No phone service)

InternetService ==> Customers internet service provider (DSL, Fiber optic, No)

OnlineSecurity ==> Whether the customer has online security or not (Yes, No, No internet service)

OnlineBackup ==> Whether the customer has online backup or not (Yes, No, No internet service)

DeviceProtection ==> Whether the customer has device protection or not (Yes, No, No internet service)

TechSupport ==> Whether the customer has tech support or not (Yes, No, No internet service)

StreamingTV ==> Whether the customer has streaming TV or not (Yes, No, No internet service)

StreamingMovies ==> Whether the customer has streaming movies or not (Yes, No, No internet service)

Contract ==> The contract term of the customer (Month-to-month, One year, Two year) PaperlessBilling ==> Whether the customer has paperless billing or not (Yes, No)

PaymentMethod ==> The customers payment method (Electronic check, Mailed check, Bank transfer (automatic), Credit card (automatic))

MonthlyCharges ==> The amount charged to the customer monthly TotalCharges ==> The total amount charged to the customer Churn ==> Whether the customer churned or not (Yes or No)

This related dataset

https://docs.google.com/spreadsheets/d/18iggDHp3K9OhD7I0AIM7OYO6VfJMMa37q_iV8bm7yes/edit?usp=sharing