How to compare machine learning models using bootstrap resampling in scikit-learn

𝘿𝙖𝙩𝙖 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝙉𝙖𝙩𝙞𝙤𝙣📊 on Instagram: "📍ENSEMBLE LEARNING – PART 10.2: BAGGING (BOOTSTRAP AGGREGATION) Bagging — short for Bootstrap Aggregation — is one of the simplest yet most powerful ensemble techniques in machine learning. Here’s how it works step-by-step 👇 1️⃣ Bootstrap Sampling: We randomly select multiple subsets of the training data with replacement. That means some samples might repeat, and some might be left out — giving each model a slightly different perspective of

What is a Bootstrap and how does it work?