Code for Regression and Classification
Python notebooks for all the computational examples about Regression and Classification from Chapter 12 of the book. See here for the full code repository.
- Premature mortality in US counties. Linear regression, ordinary least squares, coefficient of determination, explained variance
- Cartoon illustration of overfitting and generalization.
- Noise amplification in linear regression 1. Ordinary least squares, ridge regression
- Noise amplification in linear regression 2. Ordinary least squares, ridge regression
- Temperature in Versailles. Linear regression, ordinary least squares, ridge regression, sparse regression, lasso, regularization, overfitting
- Sparse regression 1. Sparsity, lasso, regularization
- Sparse regression 2. Sparsity, lasso, regularization
- Height and sex. Logistic regression, maximum likelihood, log-likelihood, logistic function
- Alzheimer’s diagnostics. Classification, logistic regression, evaluation of classification models, calibration
- Estimating wheat varieties via softmax regression.
- Digit classification. Softmax regression, overfitting, regularization
- Temperature estimation via regression trees.
- Temperature estimation via tree ensembles. Bagging, random forests, boosting, overfitting
- Log-likelihood of classification tree.
- Temperature estimation via neural networks. Regression, neural networks, deep learning, overfitting, early stopping
- Estimating wheat varieties via a classification tree.
- Estimating wheat varieties via neural networks.