Module 9: Random Forests, Neural Nets & Transformations

Topic: Random forests, neural networks, MANOVA, data transformations (log, Box-Cox, etc.).

Learning Objectives

Fit random forests with randomForest and interpret variable importance
Build a simple neural network with neuralnet
Perform MANOVA for multivariate response variables
Apply and interpret common data transformations

Slides

R Code

Key Packages

library(caret)
library(randomForest)
library(neuralnet)

Note

No class Wednesday (Thanksgiving eve). Only Monday lecture this week.

Assignment

HW9: Random Forest & Neural Networks — due Module 10 Wednesday. Submit on Canvas.

Final Assignment released this week — see Assignments.

---
title: "Module 9: Random Forests, Neural Nets & Transformations"
---

::: {.week-header}
**Topic:** Random forests, neural networks, MANOVA, data transformations (log, Box-Cox, etc.).
:::

## Learning Objectives

- Fit random forests with `randomForest` and interpret variable importance
- Build a simple neural network with `neuralnet`
- Perform MANOVA for multivariate response variables
- Apply and interpret common data transformations

## Slides

::: {.file-list}
- [L17 Random Forests & Neural Nets (PDF)](../Week%209/L17%20random%20forests%20neural%20nets.pdf)
- [L18 Transformations and MANOVA (PDF)](../Week%209/L18%20Transformations%20and%20MANOVA.pdf)
:::

## R Code

::: {.file-list}
- [L17_randomforests_neuralnets.R](../Week%209/L17_randomforests_neuralnets.R)
- [L18_transformations.R](../Week%209/L18_transformations.R)
- [L18 MANOVA.R](../Week%209/L18%20MANOVA.R)
:::

## Key Packages

```r
library(caret)
library(randomForest)
library(neuralnet)
```

## Note

::: {.callout-note}
No class Wednesday (Thanksgiving eve). Only Monday lecture this week.
:::

## Assignment

**HW9: Random Forest & Neural Networks** — due Module 10 Wednesday. Submit on Canvas.

**Final Assignment** released this week — see [Assignments](../assignments.qmd).