# XWUIChartROC

`XWUIChartROC` is a thin wrapper around `XWUIChart` with the chart `type` fixed to `'rOC'`, drawing a Receiver Operating Characteristic curve that plots true-positive rate against false-positive rate across a classifier's thresholds. Pass a `{ series }` data object - one curve per classifier - and use it to evaluate and compare binary-classification performance, where a curve bowing toward the top-left corner signals a better model. Variant and size are set through the `block` (1-4, clamped) and `size` (`sm` / `md` / `lg`) config.

## Basic Usage

This example supplies two monthly series (Series A and Series B, Jan-Jun) at `md` size, treating each as an ROC curve to lay side by side.

```example
file: examples/BasicUsage.ts
html: examples/BasicUsage.html
title: Basic Usage
description: Two monthly series (Series A and Series B, Jan-Jun) rendered as ROC curves at medium size.
```

## Model AUC Comparison

Three fraud classifiers' ROC curves overlaid for an at-a-glance AUC comparison, with a chance-level reference line marking the no-skill baseline.

```example
file: examples/ModelAUCComparison.ts
html: examples/ModelAUCComparison.html
title: Model AUC Comparison
description: Three classifiers' ROC curves, large and interactive with a legend and a chance-level line.
```

## Threshold Operating Points

A single classifier's ROC curve with each point labelled by its decision threshold, showing the true-positive vs false-positive trade-off as the cutoff moves.

```example
file: examples/ThresholdOperatingPoints.ts
html: examples/ThresholdOperatingPoints.html
title: Threshold Operating Points
description: One model's ROC with filled, threshold-labelled operating points and data labels shown.
```

```api
```