Neural Network

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Work with your assigned partner to write a Python script to fit a neural network to this used car quality data. The goal is to predict quality.

Make sure to do the following:

• Feature engineering
• Cross validation: training, dev/validation, & testing split
• Model selection (hidden layer size) based on dev/validation performance
• Use the error metrics, per class: Precision, Recall & F1
• Make a confusion matrix

How does the neural network compare to logistic regression? Repeat the experiment but change the activation function from "ReLU" to "logistic". Did that impact the results or the time it takes to fit/train the model? Compare "adam" optimizer vs "lbfgs" vs "sgd", which converged faster?

Regression with Neural Networks

Revisit the rental data, this time fit an MLPRegressor to it to predict the price. Use MAE, & MAPE to compare it to Linear Regression, which performs better or are they about the same?

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1. GFU
2. CSIS
3. J. Walker Orr
4. CSIS 441