AutoML is Automated Machine Learning, referring to processes and methods to make machine learning more accessible for a general audience. This crate builds on top of the smartcore machine learning framework, and provides some utilities to quickly train and compare models.
For instance, running the following:
rust
let mut classifier = automl::classification::Classifier::default();
classifier.with_dataset(smartcore::dataset::breast_cancer::load_dataset());
classifier.compare_models();
Will output this comparison of models usign cross-validation:
text
┌────────────────────────────────┬───────────────────┬──────────────────┐
│ Model │ Training Accuracy │ Testing Accuracy │
╞════════════════════════════════╪═══════════════════╪══════════════════╡
│ Random Forest Classifier │ 1.00 │ 0.96 │
├────────────────────────────────┼───────────────────┼──────────────────┤
│ Logistic Regression Classifier │ 0.97 │ 0.95 │
├────────────────────────────────┼───────────────────┼──────────────────┤
│ Gaussian Naive Bayes │ 0.95 │ 0.93 │
├────────────────────────────────┼───────────────────┼──────────────────┤
│ KNN Classifier │ 0.96 │ 0.92 │
├────────────────────────────────┼───────────────────┼──────────────────┤
│ Categorical Naive Bayes │ 0.96 │ 0.91 │
├────────────────────────────────┼───────────────────┼──────────────────┤
│ Decision Tree Classifier │ 1.00 │ 0.90 │
├────────────────────────────────┼───────────────────┼──────────────────┤
│ Support Vector Classifier │ 0.87 │ 0.85 │
└────────────────────────────────┴───────────────────┴──────────────────┘
You can then train a final model using classifier.train_final_model() and perform inference using that model with the predict method.
Currently this crate only has AutoML features for regression and classification. This includes the following models: - Regression - Decision Tree Regression - KNN Regression - Random Forest Regression - Linear Regression - Ridge Regression - LASSO - Elastic Net - Support Vector Regression - Classification - Random Forest Classification - Decision Tree Classification - Support Vector Classification - Logistic Regression - KNN Classification