Ranking Sample - Hotel Search Results (changed to Bing Search Engine result ranking)

samples/csharp/getting-started/Ranking_PersonalizedSort/PersonalizedRanking.sln

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+EndProject
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samples/csharp/getting-started/Ranking_PersonalizedSort/PersonalizedRanking/Common/ConsoleHelper.cs

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+using Microsoft.ML;
+using Microsoft.ML.Data;
+using PersonalizedRanking.DataStructures;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+
+namespace PersonalizedRanking.Common
+{
+    public class ConsoleHelper
+    {
+        // To evaluate the accuracy of the model's predicted rankings, prints out the Discounted Cumulative Gain and Normalized Discounted Cumulative Gain for search queries.
+        public static void EvaluateMetrics(MLContext mlContext, IDataView predictions)
+        {
+            // Evaluate the metrics for the data using NDCG; by default, metrics for the up to 3 search results in the query are reported (e.g. NDCG@3).
+            RankingMetrics metrics = mlContext.Ranking.Evaluate(predictions);
+
+            Console.WriteLine($"DCG: {string.Join(", ", metrics.DiscountedCumulativeGains.Select((d, i) => $"@{i + 1}:{d:F4}").ToArray())}");
+
+            Console.WriteLine($"NDCG: {string.Join(", ", metrics.NormalizedDiscountedCumulativeGains.Select((d, i) => $"@{i + 1}:{d:F4}").ToArray())}\n");
+        }
+
+        // Performs evaluation with the truncation level set up to 10 search results within a query.
+        // This is a temporary workaround for this issue: https://github.com/dotnet/machinelearning/issues/2728.
+        public static void EvaluateMetrics(MLContext mlContext, IDataView scoredData, int truncationLevel)
+        {
+            if (truncationLevel < 1 || truncationLevel > 10)
+            {
+                throw new InvalidOperationException("Currently metrics are only supported for 1 to 10 truncation levels.");
+            }
+
+            //  Uses reflection to set the truncation level before calling evaluate.
+            var mlAssembly = AppDomain.CurrentDomain.GetAssemblies().Where(a => a.FullName.Contains("Microsoft.ML.Data")).First();
+            var rankEvalType = mlAssembly.DefinedTypes.Where(t => t.Name.Contains("RankingEvaluator")).First();
+
+            var evalArgsType = rankEvalType.GetNestedType("Arguments");
+            var evalArgs = Activator.CreateInstance(rankEvalType.GetNestedType("Arguments"));
+
+            var dcgLevel = evalArgsType.GetField("DcgTruncationLevel");
+            dcgLevel.SetValue(evalArgs, truncationLevel);
+
+            var ctor = rankEvalType.GetConstructors().First();
+            var evaluator = ctor.Invoke(new object[] { mlContext, evalArgs });
+
+            var evaluateMethod = rankEvalType.GetMethod("Evaluate");
+            RankingMetrics metrics = (RankingMetrics)evaluateMethod.Invoke(evaluator, new object[] { scoredData, "Label", "GroupId", "Score" });
+
+            Console.WriteLine($"DCG: {string.Join(", ", metrics.DiscountedCumulativeGains.Select((d, i) => $"@{i + 1}:{d:F4}").ToArray())}");
+
+            Console.WriteLine($"NDCG: {string.Join(", ", metrics.NormalizedDiscountedCumulativeGains.Select((d, i) => $"@{i + 1}:{d:F4}").ToArray())}\n");
+        }
+
+        // Prints out the the individual scores used to determine the relative ranking.
+        public static void PrintScores(IEnumerable<SearchResultPrediction> predictions)
+        {
+            foreach (var prediction in predictions)
+            {
+                Console.WriteLine($"GroupId: {prediction.GroupId}, Score: {prediction.Score}");
+            }
+        }
+    }
+}