Classical Supervised LearningLevel: FoundationalStudy Battlecard

Decision Trees (CART)

Recursive Binary Partitioning with Gini Impurity, Entropy & Tree Pruning

#Trees#Non-linear#Interpretability#Gini#Entropy#CART
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STAGE 1 / 7— Anti-Pattern
Section 1: The LLM Anti-Pattern vs Right-Sized Model
The Naive Generative LLM Approach:

Prompting an LLM to follow a 20-step conditional rulebook for insurance eligibility.

Why It Fails in Production:

LLMs hallucinate logic, forget nested if-else constraints midway through the generation, and cannot be audited for regulatory compliance.

Targeted Algorithm (Decision Trees (CART))
Latency:0.01ms
Cost / 1M Ops:$0.00
Determinism:100% Deterministic Rule Engine
Generative LLM Alternative
Latency:2,000ms
Cost / 1M Ops:$5,000
Determinism:Prone to Rule Skips