# Machine Learning

- How to Read a Standard R Table
- How to Convert a Predictive Model Simulator into an Allocation Tool for New Data
- How to Create Diagnostic Reports for Latent Class, Mixed Mode Trees, and Mixed Mode Cluster Analysis
- How to Save Machine Learning Probability of Each Response Variable
- How to Save Machine Learning Predicted Values Variables
- How to Save Machine Learning Discrimination Variables
- How to Run Machine Learning Diagnostics - Prediction-Accuracy Table
- How to Run Machine Learning Diagnostics - Table of Discriminant Function Coefficients Extension
- How to Run Mixed-Mode Tree
- How to Run Machine Learning Linear Discriminant Analysis
- How to Run Support Vector Machine
- How to Run Random Forest
- How to Run a Gradient Boosting Machine Learning Model
- How to Create an Ensemble of Machine Learning Models
- How to Run Deep Learning
- How to Compare Machine Learning Models
- How to Create a Prediction-Accuracy Table from Classification And Regression Tree (CART)
- How to Save Variables from a Classification And Regression Tree (CART)
- How to Create a Classification And Regression Trees (CART)
- How to Save Probabilities of Each Response from a Machine Learning Model
- How to Save the Predicted Values from a Machine Learning Model
- How to Save Discriminant Variables From an LDA Output
- How to Do Gradient Boosting Analysis