LogisticRegression

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Train a Logistic Regression model and use it to predict unknown classifiers.  You supply data of arbitrary number of features to train the model.  Once trained, the model can be used to classify test data.  The predicted results, as well as an accuracy measure, are returned to the user.   The input must be formatted as a dictionary  {'X_train' : [x_train_data], 'y_train' : [y_train_data], 'X_test' : [x_test_data]}  X_train should be a matrix of size (n_samples, n_features), y_train should be a list of size (n_samples,), X_test must have the same number of features as X_train

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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/ryval/LogisticRegression/0.1.2
View cURL Docs
algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://ryval/LogisticRegression/0.1.2 -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://ryval/LogisticRegression/0.1.2");
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://ryval/LogisticRegression/0.1.2")
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://ryval/LogisticRegression/0.1.2")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://ryval/LogisticRegression/0.1.2")
           .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('ryval/LogisticRegression/0.1.2')
print algo.pipe(input)
View Python Docs
library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("ryval/LogisticRegression/0.1.2")
result <- algo$pipe(input)$result
print(result)
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('ryval/LogisticRegression/0.1.2')
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('ryval/LogisticRegression/0.1.2');
let response = algo.pipe(input);
View Rust Docs
Discussion
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