As we’ve seen from the previous post that the target variable Churn is imbalanced. We have about 27% churn records in the Telco Customer Churn data. It is not a highly imbalanced dataset. I typically would deal with the imbalance issue if the minority class is 10% or less. But want to use this data… Read More »
When we first look at some data, we will want to understand them. It’s an essential step before any type of modeling to explore the data and understand the data first. From exploratory data analysis, we can discover patterns. Patterns in the data provide clues about relationships. If a systematic relationship exists between two variables… Read More »
I love charts. And I believe one of the criteria to separate a great analyst from a OK analyst, a great data scientist from a OK data scientist is whether the analyst or data scientist can convey the information in a chart that’s very intuitive and little brain power is needed for the audience to… Read More »