Merge pull request #6689 from jaymathe/dp2-jm

2 additional ML articles with C# code edit
andyhammar · Jan 15, 2015 · d299780 · d299780
2 parents 449ca74 + a799342
commit d299780
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Showing 2 changed files with 47 additions and 50 deletions.
diff --git a/articles/machine-learning-r-csharp-cluster-model.md b/articles/machine-learning-r-csharp-cluster-model.md
@@ -26,37 +26,36 @@ There are multiple ways of consuming the service in an automated fashion (an exa
 
 ###Starting C# code for web service consumption:
 
-	public class Input{
-	public double Recency;
-	public double Frequency;
-	public double Monetary;
-	public double Time;
-	public double Class;
+	    public class Input
+	    {
+	        public string value;
+	        public string k;
+	    }
+
+	    public AuthenticationHeaderValue CreateBasicHeader(string username, string password)
+	    {
+	        byte[] byteArray = System.Text.Encoding.UTF8.GetBytes(username + ":" + password);
+	        return new AuthenticationHeaderValue("Basic", Convert.ToBase64String(byteArray));
 	}
-
-	public AuthenticationHeaderValue CreateBasicHeader(string username, string password)
-    {
-        byte[] byteArray = System.Text.Encoding.UTF8.GetBytes(username + ":" + password);
-        System.Diagnostics.Debug.WriteLine("AuthenticationHeaderValue" + new AuthenticationHeaderValue("Basic", Convert.ToBase64String(byteArray)));
-        return new AuthenticationHeaderValue("Basic", Convert.ToBase64String(byteArray));
-    }
-       
+
 	void Main()
 	{
-  	var input = new Input(){Recency =1, Frequency=0,Monetary=0,Time=1, Class= 0};
-	var json = JsonConvert.SerializeObject(input);
-	var acitionUri =  "PutAPIURLHere,e.g.https://api.datamarket.azure.com/..../v1/Score";
-
-  	var httpClient = new HttpClient();
-   	httpClient.DefaultRequestHeaders.Authorization = CreateBasicHeader("PutEmailAddressHere","ChangeToAPIKey");
-   	httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
-  	var query = httpClient.PostAsync(acitionUri,new StringContent(json));
-  	var result = query.Result.Content;
-  	var scoreResult = result.ReadAsStringAsync().Result;
-  	scoreResult.Dump();
+	        var input = new Input() { value = TextBox1.Text, k = TextBox2.Text };
+	        var json = JsonConvert.SerializeObject(input);
+	        var acitionUri = "PutAPIURLHere,e.g.https://api.datamarket.azure.com/..../v1/Score";
+	        var httpClient = new HttpClient();
+	
+	        httpClient.DefaultRequestHeaders.Authorization = CreateBasicHeader("PutEmailAddressHere", "ChangeToAPIKey");
+	        httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
+	
+	        var response = httpClient.PostAsync(acitionUri, new StringContent(json));
+	        var result = response.Result.Content;
+	    var scoreResult = result.ReadAsStringAsync().Result;
 	}
 
 
+
+
 #Creation of the web-service  
 >This web service was created using Azure ML. For a free trial, as well as introductory videos on creating experiments and [publishing web services](http://azure.microsoft.com/en-us/documentation/articles/machine-learning-publish-web-service-to-azure-marketplace/), please see [azure.com/ml](http://azure.com/ml). Below is a screenshot of the experiment that created the web service and example code for each of the modules within the experiment.
 

diff --git a/articles/machine-learning-r-csharp-multivariate-linear-regression.md b/articles/machine-learning-r-csharp-multivariate-linear-regression.md
@@ -27,37 +27,35 @@ There are multiple ways of consuming the service in an automated fashion (an exa
 
 ###Starting C# code for web service consumption:
 
-	public class Input{
-	public double Recency;
-	public double Frequency;
-	public double Monetary;
-	public double Time;
-	public double Class;
+	    public class Input
+	    {
+	        public string value;
 	}
-
-	public AuthenticationHeaderValue CreateBasicHeader(string username, string password)
-    {
-        byte[] byteArray = System.Text.Encoding.UTF8.GetBytes(username + ":" + password);
-        System.Diagnostics.Debug.WriteLine("AuthenticationHeaderValue" + new AuthenticationHeaderValue("Basic", Convert.ToBase64String(byteArray)));
-        return new AuthenticationHeaderValue("Basic", Convert.ToBase64String(byteArray));
-    }
-       
+
+	    public AuthenticationHeaderValue CreateBasicHeader(string username, string password)
+	    {
+	        byte[] byteArray = System.Text.Encoding.UTF8.GetBytes(username + ":" + password);
+	        return new AuthenticationHeaderValue("Basic", Convert.ToBase64String(byteArray));
+	}
+
 	void Main()
 	{
-  	var input = new Input(){Recency =1, Frequency=0,Monetary=0,Time=1, Class= 0};
-	var json = JsonConvert.SerializeObject(input);
-	var acitionUri =  "PutAPIURLHere,e.g.https://api.datamarket.azure.com/..../v1/Score";
-
-  	var httpClient = new HttpClient();
-   	httpClient.DefaultRequestHeaders.Authorization = CreateBasicHeader("PutEmailAddressHere","ChangeToAPIKey");
-   	httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
-  	var query = httpClient.PostAsync(acitionUri,new StringContent(json));
-  	var result = query.Result.Content;
-  	var scoreResult = result.ReadAsStringAsync().Result;
-  	scoreResult.Dump();
+	        var input = new Input() { value = TextBox1.Text };
+	        var json = JsonConvert.SerializeObject(input);
+	        var acitionUri = "PutAPIURLHere,e.g.https://api.datamarket.azure.com/..../v1/Score";
+	        var httpClient = new HttpClient();
+	
+	        httpClient.DefaultRequestHeaders.Authorization = CreateBasicHeader("PutEmailAddressHere", "ChangeToAPIKey");
+	        httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
+	
+	        var response = httpClient.PostAsync(acitionUri, new StringContent(json));
+	        var result = response.Result.Content;
+	    var scoreResult = result.ReadAsStringAsync().Result;
 	}
 
 
+
+
 #Creation of the web-service  
 >This web service was created using Azure ML. For a free trial, as well as introductory videos on creating experiments and [publishing web services](http://azure.microsoft.com/en-us/documentation/articles/machine-learning-publish-web-service-to-azure-marketplace/), please see [azure.com/ml](http://azure.com/ml). Below is a screenshot of the experiment that created the web service and example code for each of the modules within the experiment.