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https://github.com/ankane/trend-api
Anomaly detection and forecasting API
https://github.com/ankane/trend-api
Last synced: about 19 hours ago
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Anomaly detection and forecasting API
- Host: GitHub
- URL: https://github.com/ankane/trend-api
- Owner: ankane
- License: gpl-3.0
- Created: 2020-01-31T22:31:40.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2024-11-12T06:49:36.000Z (about 1 month ago)
- Last Synced: 2024-11-24T21:03:46.954Z (18 days ago)
- Language: R
- Size: 57.6 KB
- Stars: 90
- Watchers: 3
- Forks: 10
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
Awesome Lists containing this project
- jimsghstars - ankane/trend-api - Anomaly detection and forecasting API (R)
README
# Trend
An anomaly detection and forecasting API. Get started quickly with state-of-the-art algorithms.
## Installation
### Docker
An image is available on [Docker Hub](https://hub.docker.com/r/ankane/trend/). Run:
```sh
docker run -ti -p=8000:8000 ankane/trend
```
### Non-Docker
Download the latest code
```sh
git clone https://github.com/ankane/trend-api.git
cd trend-api
```
Install [Jetpack](https://github.com/ankane/jetpack) and run:
```sh
Rscript -e 'jetpack::install()'
```
And start the server
```sh
Rscript server.R
```
## Anomaly Detection
Detect anomalies in a time series.
- Works with dates and times
- Accounts for seasonality and trend
- Robust to missing values
The current version uses STL with [multiple seasonal components](https://otexts.org/fpp2/complexseasonality.html#stl-with-multiple-seasonal-periods) for decomposition.
```http
POST /anomalies HTTP/1.1
Host: trendapi.org
Content-Type: application/json
{
"series": {
"2025-01-01": 150,
"2025-01-02": 125,
"2025-01-03": 133
}
}
```
Returns JSON structured like this:
```json
{
"anomalies": [
"2025-01-10",
"2025-01-13"
]
}
```
## Forecasting
Get future predictions for a time series.
- Works with dates and times
- Accounts for seasonality and trend
- Robust to missing values
- No need to remove outliers beforehand
The current version uses [TBATS](https://robjhyndman.com/papers/ComplexSeasonality.pdf) for predictions.
```http
POST /forecast HTTP/1.1
Host: trendapi.org
Content-Type: application/json
{
"series": {
"2025-01-01": 150,
"2025-01-02": 125,
"2025-01-03": 133
},
"count": 3
}
```
Returns JSON structured like this:
```json
{
"forecast": {
"2025-03-01": 137.5,
"2025-03-02": 122.9,
"2025-03-03": 144.1
}
}
```
If you get a [flat or linear forecast](https://robjhyndman.com/hyndsight/flat-forecasts/), this is expected. It means no seasonality is detected in the series.
## Correlation (Experimental)
Get the correlation between two time series.
The current version uses [normalized cross correlation](https://en.wikipedia.org/wiki/Cross-correlation#Time_series_analysis).
```http
POST /correlation HTTP/1.1
Host: trendapi.org
Content-Type: application/json
{
"series": {
"2025-01-01": 150,
"2025-01-02": 125,
"2025-01-03": 133
},
"series2": {
"2025-01-01": 150,
"2025-01-02": 176,
"2025-01-03": 145
}
}
```
Returns JSON structured like this:
```json
{
"correlation": 0.95
}
```
## Errors
The API uses HTTP status codes to indicate errors.
Code | Description
--- | ---
400 | There’s an issue with the request parameters
500 | There’s an issue with the server
The body will contain details about the specific error.
```json
{
"error": "Missing parameter: series"
}
```
## Clients
A client library is available for [Ruby](https://github.com/ankane/trend).
Here’s an example with jQuery:
```js
var series = {}, i, date, data;
for (i = 1; i < 30; i++) {
date = new Date(2025, 1, i);
series[date.toISOString()] = date.getDay();
}
data = {series: series};
$.post("https://trendapi.org/forecast", data, function(resp) {
console.log(resp);
}, "json");
```
## Credits
A special thanks to [Rob J Hyndman](https://robjhyndman.com) for his incredible work on forecasting. Learn more about the topic from his [free online book](https://otexts.org/fpp2/).
## History
View the [changelog](https://github.com/ankane/trend-api/blob/master/CHANGELOG.md)
## Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- [Report bugs](https://github.com/ankane/trend-api/issues)
- Fix bugs and [submit pull requests](https://github.com/ankane/trend-api/pulls)
- Write, clarify, or fix documentation
- Suggest or add new features