## Anomaly detection types

Kloudfuse provides four Anomaly detection algorithms that overlay a probabilistic band on the metric, and display the expected behavior of a series based on past values.

### basic

Implements the [Rolling Quantile](https://docs.kloudfuse.com/platform/3.2.5/rolling-quantile/) algorithm.

**Sampling interval:** 1m, 2m, 3m, 5m, 10m, 15m, 30m, 1h, and 2h.

**Numeric parameter:** has the possible values of 1, 2, or 3.

### agile

Implements the [SARIMA](https://docs.kloudfuse.com/platform/3.2.5/sarima/) algorithm.

**Numeric parameter:** has the possible values of 1, 2, or 3.

### robust

Implements the [Seasonal decompose](https://docs.kloudfuse.com/platform/3.2.5/seasonal-decompose/) algorithm.

**Sampling interval:** 1m, 2m, 3m, 5m, 10m, 15m, 30m, 1h, and 2h.

**Numeric parameter:** has the possible values of 1, 2, or 3.

### agile-robust

Implements the [Prophet](https://docs.kloudfuse.com/platform/3.2.5/prophet/) algorithm.

**Sampling interval:** hourly, daily, or weekly.
**Numeric parameter:** has the possible values of 1, 2, or 3.