Weka Classification

No algorithm description given

This is the main algorithm that all of the Weka classification algorithms call. It is preferred that you do not call this algorithm directly, but by one of the classifiers on the platform. The Weka algorithms that are on the platform take in flat Json as input. It is assumed that any data that is going to be used with these algorithms will be large in size, so all interaction is done through Data collections. You can look at the DigitRecognition algorithm we made for a quick demo of how to use Weka algorithms. That algorithm takes in either a matrix or an array of doubles that represent a black and white picture. The picture is a hand-drawn digit, and we feed it to a pretrained model on the MNIST dataset that will classify which of the 10 digits this particular one is.

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Internet access

This algorithm has Internet access. This is necessary for algorithms that rely on external services, however it also implies that this algorithm is able to send your input data outside of the Algorithmia platform.


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

1. Type your input

2. See the result

Running algorithm...

3. Use this 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/weka/WekaClassification/0.1.9
View cURL Docs
algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://weka/WekaClassification/0.1.9 -d '{{input | formatInput:"cli"}}'
View CLI 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://weka/WekaClassification/0.1.9");
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://weka/WekaClassification/0.1.9")
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://weka/WekaClassification/0.1.9")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://weka/WekaClassification/0.1.9")
           .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('weka/WekaClassification/0.1.9')
print algo.pipe(input)
View Python Docs
library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("weka/WekaClassification/0.1.9")
result <- algo$pipe(input)$result
print(result)
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('weka/WekaClassification/0.1.9')
puts algo.pipe(input).result
View Ruby Docs
use algorithmia::*;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo('weka/WekaClassification/0.1.9');
let response = algo.pipe(input);
View Rust Docs
Discussion
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