Predict with Rust

1. Install.

[dependencies] tangram = "*"

2. Predict.

First, import the tangram library and load the model file. Then, make an object with info for a new patient that matches the CSV, excluding the diagnosis column. Finally, call predict and print out the result.

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fn main() { // Load the model from the path. let model: tangram::Model = tangram::Model::from_path("heart_disease.tangram", None).unwrap(); // Create an example input matching the schema of the CSV file the model was trained on. // Here the data is just hard-coded, but in your application you will probably get this // from a database or user input. let input = tangram::predict_input! { "age": 63.0, "gender": "male", "chest_pain": "typical angina", "resting_blood_pressure": 145.0, "cholesterol": 233.0, "fasting_blood_sugar_greater_than_120": "true", "resting_ecg_result": "probable or definite left ventricular hypertrophy", "exercise_max_heart_rate": 150.0, "exercise_induced_angina": "no", "exercise_st_depression": 2.3, "exercise_st_slope": "downsloping", "fluoroscopy_vessels_colored": 0.0, "thallium_stress_test": "fixed defect", }; // Make the prediction! let output = model.predict_one(input, None); // Print the output. println!("Output: {:?}", output); }