# training_evaluation

> PyHealth provides comprehensive tools for training models, evaluating predictions, ensuring model reliability, and interpreting results for clinical applic

- Source: https://doutorai.pt/en/components/skills__training-evaluation
- Type: Skills
- Category: Scientific
- Downloads: 0
- Site: Doutor AI (https://doutorai.pt/en) - AI tools for small businesses

An open-source community component, curated and adapted by Doutor AI.

## What it does and how to use it

A **skill** that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.

1. Install the skill (command above).
2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
3. No commands to memorize: you talk in plain language and the skill does the rest.

## Install (Claude Code)

```bash
mkdir -p .claude/skills/training-evaluation && curl -fsSL https://doutorai.pt/data/lib/skills__training-evaluation.md -o .claude/skills/training-evaluation/SKILL.md
```

Paste this command into the terminal, in your project folder, and the component installs automatically.

## Content

````
# PyHealth Training, Evaluation, and Interpretability

## Overview

PyHealth provides comprehensive tools for training models, evaluating predictions, ensuring model reliability, and interpreting results for clinical applications.

## Trainer Class

### Core Functionality

The `Trainer` class manages the complete model training and evaluation workflow with PyTorch integration.

**Initialization:**
```python
from pyhealth.trainer import Trainer

trainer = Trainer(
    model=model,  # PyHealth or PyTorch model
    device="cuda",  # or "cpu"
)
```

### Training

**train() method**

Trains models 

- 🔒 Full content on the Pro plan (€7.99/month) -
````

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Content by Doutor AI (https://doutorai.pt/en). When quoting, please cite the source: https://doutorai.pt/en/components/skills__training-evaluation