Discriminant Analysis
Homework 3 explores Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) applied to golf shot data. Visualize decision boundaries and understand the geometric interpretation of these methods.
Learning Objectives
- Derive and implement Linear Discriminant Analysis
- Understand when QDA outperforms LDA
- Visualize and interpret decision boundaries
- Apply Bayes' theorem to classification
ESLII Reference
This homework covers Chapter 4 (Linear Methods for Classification), focusing on discriminant analysis methods and their geometric interpretation.
Available Scripts
| Script | Description | Subdirectory |
|---|---|---|
golf_analysis_complete.py |
Full LDA/QDA analysis on golf shot data | DA/ |
golf_analysis_main.py |
Main analysis script with visualization | DA/ |
golf_report_generator.py |
Generate formatted analysis reports | DA/ |
Quick Start
# CLI exploration
cd domains/Stan/cli
python main.py "homework 3"
# Cockpit GUI
cd domains/Stan/cockpit
python stan_cockpit.py
# Enter: "explore discriminant analysis golf"
# Direct tool access
from unified_agent import StanDataClient, ToolRegistry
client = StanDataClient()
tools = ToolRegistry(client)
result = tools.get_tool('load_hmk3_info')({})
Related Tools
| Tool | Description |
|---|---|
load_hmk3_info |
Get Homework 3 metadata and available scripts |
list_hmk3_scripts |
List all Python scripts in the Hmk3/DA directory |
find_by_technique |
Search homeworks by technique (e.g., "LDA") |