Neural Network Series in R
While developing these demonstrations in logistic regression and neural networks, I used and discovered some interesting methods and techniques:
A few useful commands and packages...:
- update.packages() for updating installed packages in one easy action
- as.formula() for creating a formula that I can reuse and update in one action across all my code sections
- View() for looking at data frames
- fourfoldplot() for plotting confusion matrices
- neuralnet for developing neural networks
- caret, used with nnet, to create predictive model
- plotnet() in NeuralNetTools, for creating attractive neural network models
Resources that I used or that I would like to explore...
- MS Azure Notebooks, for working online with Python, R, and F#, all part of MS's data workflows
- Efficient R Programming, that seems to have many good tips on working with R
- Data Mining Algorithms in SSAS, Excel, and R, showing various algorithms in each technology
- R Documentation, a high quality, useable resource
To explore this series...