Cost complexity pruning ccp скачать в хорошем качестве

Cost complexity pruning ccp

Download 1M+ code from https://codegive.com/f91829a okay, let's dive into cost complexity pruning (ccp), a crucial technique for simplifying decision trees and improving their generalization performance. i'll provide a comprehensive tutorial with a code example in python using `scikit-learn`. *i. introduction: the problem of overfitting in decision trees* decision trees are powerful machine learning algorithms known for their interpretability and ability to capture complex relationships in data. however, they are also prone to overfitting*. overfitting happens when a model learns the training data *too well, including noise and specific quirks, and consequently performs poorly on new, unseen data. a fully grown decision tree, built without any constraints, can perfectly classify all training samples. this perfect classification comes at a cost: a complex tree structure that memorizes the training data rather than learning the underlying patterns. this leads to high variance and poor generalization. *ii. cost complexity pruning (ccp) – a solution* cost complexity pruning (ccp), also known as *weakest link pruning*, addresses overfitting by selectively removing branches from a decision tree. the goal is to find a smaller, simpler tree that sacrifices some accuracy on the training data in exchange for improved performance on unseen data. *iii. the core concepts of ccp* 1. *cost complexity:* the core idea of ccp revolves around a "cost complexity" parameter, often denoted by `alpha` (α). `alpha` controls the trade-off between the tree's size (number of leaves) and its accuracy. it essentially penalizes complex trees. 2. *the pruning process:* ccp works iteratively. starting with the fully grown tree, it identifies the "weakest link" at each step – the branch that contributes the least to the overall accuracy, relative to its complexity. this branch is then pruned (removed), creating a slightly smaller tree. the algorithm continues this pruning process, generating a sequence of pr ... #CostComplexityPruning #CCP #DecisionTrees cost complexity pruning CCP decision trees pruning techniques model optimization overfitting reduction tree complexity accuracy improvement machine learning algorithm efficiency bias-variance tradeoff CART algorithm model selection regularization methods statistical learning