Threshold Anomaly Detection - Algorithm by TimeSeries

No algorithm description given

Threshold Anomaly Detection This algorithm detects out of bounds data-points from a time-series dataset and sets them to 0. Table of Contents Introduction Inputs Outputs Algorithm Console Introduction By using the pre-defined upper & lower bounds, this algorithm will keep all data-points that lie within the thresholds. All data-points that lie outside are set to 0. Inputs This algorithm has two input formats; JSON Formatting and Array Formatting. JSON Format { 
 "data": Double[],
 "lowerBound": Double,
 "upperBound": Double
} { 
 "data": [1,2,3,4,3,4,6,7,5,4,2,1,1],
 "lowerBound": 1.4,
 "upperBound": 6.5
} data - (required) - The time series input data you wish to detect anomalies on, this algorithm assumes the values are evenly spaced. ( dx(1) == dx(n) ) lowerBound - (optional) - The lower boundary limit, the default value is 0. upperBound - (optional) - The upper boundary limit, the default value is 0. Array Format [
 data: Double[],
 lowerBound: Double,
 upperBound: Double
] [[1,2,3,4,3,4,6,7,5,4,2,1,1], 1.4, 6.5] data - (required) - The time-series input data you wish to detect anomalies on, this algorithm assumes the values are evenly spaced. ( dx(1) == dx(n) ) lowerBound - (required) - The lower boundary limit. upperBound - (required) - The upper boundary limit. Outputs This algorithm has json output for json input, and array output for array input. JSON Format { 
 "output": Double[]
} { 
 "output": [0,2,3,4,3,4,6,0,5,4,2,0,0]
} output - The filtered dataset, if a data-point was considered out of bounds it’s value is set to 0. Array Format output: Double[] [0,2,3,4,3,4,6,0,5,4,2,0,0] output - The filtered dataset, if a datapoint was considered out of bounds it’s value is set to 0.

Tags

(no tags)

Cost Breakdown

0 cr

royalty per call

1 cr

usage per second

avg duration

Cost Calculator

API call duration (sec)

API calls

Estimated cost

per calls

for large volume discounts

For additional details on how pricing works, see Algorithmia pricing.

No permissions required

This algorithm does not require any special permissions.

To understand more about how algorithm permissions work, see the permissions documentation.

1. Type your input

2. See the result

Running algorithm...

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY' https://api.algorithmia.com/v1/algo/TimeSeries/ThresholdAnomalyDetection/0.2.0

View cURL Docs

algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://TimeSeries/ThresholdAnomalyDetection/0.2.0 -d '{{input | formatInput:"cli"}}'

View CLI Docs

import (
  algorithmia "github.com/algorithmiaio/algorithmia-go"
)

input := {{input | formatInput:"go"}}

var client = algorithmia.NewClient("YOUR_API_KEY", "")
algo, _ := client.Algo("algo://TimeSeries/ThresholdAnomalyDetection/0.2.0")
resp, _ := algo.Pipe(input)
response := resp.(*algorithmia.AlgoResponse)
fmt.Println(response.Result)

View Go Docs

import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://TimeSeries/ThresholdAnomalyDetection/0.2.0");
AlgoResponse result = algo.pipeJson(input);
System.out.println(result.asJsonString());

View Java Docs

import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://TimeSeries/ThresholdAnomalyDetection/0.2.0")
val result = algo.pipeJson(input)
System.out.println(result.asJsonString)

View Scala Docs

var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://TimeSeries/ThresholdAnomalyDetection/0.2.0")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });

View Javascript Docs

using Algorithmia;

var input = "{{input | formatInput:"cs"}}";
var client = new Client("YOUR_API_KEY");
var algorithm = client.algo("algo://TimeSeries/ThresholdAnomalyDetection/0.2.0");
var response = algorithm.pipe<object>(input);
Console.WriteLine(response.result);

View .NET/C# Docs

var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://TimeSeries/ThresholdAnomalyDetection/0.2.0")
           .pipe(input)
           .then(function(response) {
             console.log(response.get());
           });

View NodeJS Docs

import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('TimeSeries/ThresholdAnomalyDetection/0.2.0')
print algo.pipe(input)

View Python Docs

library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("TimeSeries/ThresholdAnomalyDetection/0.2.0")
result <- algo$pipe(input)$result
print(result)

View R Docs

require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('TimeSeries/ThresholdAnomalyDetection/0.2.0')
puts algo.pipe(input).result

View Ruby Docs

use algorithmia::Algorithmia;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo("TimeSeries/ThresholdAnomalyDetection/0.2.0");
let response = algo.pipe(input);

View Rust Docs

import Algorithmia

let input = "{{input | formatInput:"swift"}}";
let client = Algorithmia.client(simpleKey: "YOUR_API_KEY")
let algo = client.algo(algoUri: "TimeSeries/ThresholdAnomalyDetection/0.2.0") { resp, error in
  print(resp)
}

View Swift Docs

Discussion