The next part is also divided into two parts. First I give a brief introduction to decision trees, how a decision tree look like. The last section is about how to train a decision tree. The second part will be about overfitting a decision tree and how to control the size of a tree. DecisionContinue reading “ML Zoomcamp 2023 – Decision Trees and Ensemble Learning– Part 4”
Category Archives: Decision Trees
ML Zoomcamp 2023 – Decision Trees and Ensemble Learning– Part 3
Building upon the necessary preparation steps outlined in the previous article, this section is dedicated to two critical processes: re-encoding categorical variables and performing the train/validation/test split, a crucial step in preparing our data for modeling and evaluation. Data cleaning and preparation – Data Transformation and Splitting – Part 2/2 Re-encoding the categorical variables ToContinue reading “ML Zoomcamp 2023 – Decision Trees and Ensemble Learning– Part 3”
ML Zoomcamp 2023 – Decision Trees and Ensemble Learning– Part 2
In part 1 of this chapter, “Decision Trees and Ensemble Learning,” we introduced the project, which is a binary classification problem aimed at predicting the probability of a client defaulting on a loan. Part 2 of this chapter is divided into two main sections. Preparation Steps In the first part, we focus on necessary preparationContinue reading “ML Zoomcamp 2023 – Decision Trees and Ensemble Learning– Part 2”
ML Zoomcamp 2023 – Decision Trees and Ensemble Learning– Part 1
Credit Risk Scoring Project The project for this week involves credit risk scoring. Imagine you want to buy a mobile phone, so you visit your bank to apply for a loan. You fill out an application form that requests various details, such as your income, the price of the phone, and the loan amount youContinue reading “ML Zoomcamp 2023 – Decision Trees and Ensemble Learning– Part 1”
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