Binary splitting

Binary splitting is a method used primarily in statistical modeling and machine learning to create decision trees or partition data into subsets based on the values of certain features. The process involves the following key steps: 1. **Initialization**: Start with the whole dataset. 2. **Choosing a Split**: Identify potential splits based on the features of the data. For each feature, determine thresholds that can best separate the data into two groups (or child nodes).