Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

One name for MulticlassClassification #2919

Merged
merged 12 commits into from
Mar 13, 2019
Prev Previous commit
Next Next commit
find and replace MultiClass to Multiclass
  • Loading branch information
artidoro committed Mar 13, 2019

Unverified

This user has not yet uploaded their public signing key.
commit 955f2fdc95d5ea794eac335ef2f6b9a66f9b26d8
Original file line number Diff line number Diff line change
@@ -9,7 +9,7 @@ namespace Microsoft.ML.Samples.Static
{
class LightGBMMulticlassWithInMemoryData
{
public void MultiClassLightGbmStaticPipelineWithInMemoryData()
public void MulticlassLightGbmStaticPipelineWithInMemoryData()
{
// Create a general context for ML.NET operations. It can be used for exception tracking and logging,
// as a catalog of available operations and as the source of randomness.
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Core/Data/AnnotationUtils.cs
Original file line number Diff line number Diff line change
@@ -87,7 +87,7 @@ public static class Const
public static class ScoreColumnKind
{
public const string BinaryClassification = "BinaryClassification";
public const string MultiClassClassification = "MultiClassClassification";
public const string MulticlassClassification = "MultiClassClassification";
artidoro marked this conversation as resolved.
Show resolved Hide resolved
public const string Regression = "Regression";
public const string Ranking = "Ranking";
public const string Clustering = "Clustering";
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Core/Prediction/IPredictor.cs
Original file line number Diff line number Diff line change
@@ -19,7 +19,7 @@ internal enum PredictionKind
Custom = 1,

BinaryClassification = 2,
MultiClassClassification = 3,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Core/Prediction/ITrainer.cs
Original file line number Diff line number Diff line change
@@ -19,7 +19,7 @@ namespace Microsoft.ML
[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMultiClassClassifierTrainer();
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Data/DataLoadSave/TransformerChain.cs
Original file line number Diff line number Diff line change
@@ -277,7 +277,7 @@ public static TransformerChain<ITransformer> LoadFrom(IHostEnvironment env, Stre
if (predictor.PredictionKind == PredictionKind.BinaryClassification)
pred = new BinaryPredictionTransformer<IPredictorProducing<float>>(env, predictor as IPredictorProducing<float>, chain.Schema,
roles.Where(x => x.Key.Value == RoleMappedSchema.ColumnRole.Feature.Value).First().Value);
else if (predictor.PredictionKind == PredictionKind.MultiClassClassification)
else if (predictor.PredictionKind == PredictionKind.MulticlassClassification)
pred = new MulticlassClassificationPredictionTransformer<IPredictorProducing<VBuffer<float>>>(env,
predictor as IPredictorProducing<VBuffer<float>>, chain.Schema,
roles.Where(x => x.Key.Value == RoleMappedSchema.ColumnRole.Feature.Value).First().Value,
6 changes: 3 additions & 3 deletions src/Microsoft.ML.Data/EntryPoints/InputBuilder.cs
Original file line number Diff line number Diff line change
@@ -839,11 +839,11 @@ public static class PipelineSweeperSupportedMetrics
{
public static new string ToString() => "SupportedMetric";
public const string Auc = BinaryClassifierEvaluator.Auc;
public const string AccuracyMicro = Data.MultiClassClassificationEvaluator.AccuracyMicro;
public const string AccuracyMacro = MultiClassClassificationEvaluator.AccuracyMacro;
public const string AccuracyMicro = Data.MulticlassClassificationEvaluator.AccuracyMicro;
public const string AccuracyMacro = MulticlassClassificationEvaluator.AccuracyMacro;
public const string F1 = BinaryClassifierEvaluator.F1;
public const string AuPrc = BinaryClassifierEvaluator.AuPrc;
public const string TopKAccuracy = MultiClassClassificationEvaluator.TopKAccuracy;
public const string TopKAccuracy = MulticlassClassificationEvaluator.TopKAccuracy;
public const string L1 = RegressionLossEvaluatorBase<MultiOutputRegressionEvaluator.Aggregator>.L1;
public const string L2 = RegressionLossEvaluatorBase<MultiOutputRegressionEvaluator.Aggregator>.L2;
public const string Rms = RegressionLossEvaluatorBase<MultiOutputRegressionEvaluator.Aggregator>.Rms;
2 changes: 1 addition & 1 deletion src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs
Original file line number Diff line number Diff line change
@@ -40,7 +40,7 @@ public static Dictionary<string, Func<IHostEnvironment, IMamlEvaluator>> Instanc
var tmp = new Dictionary<string, Func<IHostEnvironment, IMamlEvaluator>>
{
{ AnnotationUtils.Const.ScoreColumnKind.BinaryClassification, env => new BinaryClassifierMamlEvaluator(env, new BinaryClassifierMamlEvaluator.Arguments()) },
{ AnnotationUtils.Const.ScoreColumnKind.MultiClassClassification, env => new MultiClassClassificationMamlEvaluator(env, new MultiClassClassificationMamlEvaluator.Arguments()) },
{ AnnotationUtils.Const.ScoreColumnKind.MulticlassClassification, env => new MulticlassClassificationMamlEvaluator(env, new MulticlassClassificationMamlEvaluator.Arguments()) },
{ AnnotationUtils.Const.ScoreColumnKind.Regression, env => new RegressionMamlEvaluator(env, new RegressionMamlEvaluator.Arguments()) },
{ AnnotationUtils.Const.ScoreColumnKind.MultiOutputRegression, env => new MultiOutputRegressionMamlEvaluator(env, new MultiOutputRegressionMamlEvaluator.Arguments()) },
{ AnnotationUtils.Const.ScoreColumnKind.QuantileRegression, env => new QuantileRegressionMamlEvaluator(env, new QuantileRegressionMamlEvaluator.Arguments()) },
Original file line number Diff line number Diff line change
@@ -12,7 +12,7 @@ namespace Microsoft.ML.Data
/// <summary>
/// Evaluation results for multi-class classification trainers.
/// </summary>
public sealed class MultiClassClassificationMetrics
public sealed class MulticlassClassificationMetrics
{
/// <summary>
/// Gets the average log-loss of the classifier.
@@ -83,22 +83,22 @@ public sealed class MultiClassClassificationMetrics
/// </remarks>
public IReadOnlyList<double> PerClassLogLoss { get; }

internal MultiClassClassificationMetrics(IExceptionContext ectx, DataViewRow overallResult, int topK)
internal MulticlassClassificationMetrics(IExceptionContext ectx, DataViewRow overallResult, int topK)
{
double FetchDouble(string name) => RowCursorUtils.Fetch<double>(ectx, overallResult, name);
MicroAccuracy = FetchDouble(MultiClassClassificationEvaluator.AccuracyMicro);
MacroAccuracy = FetchDouble(MultiClassClassificationEvaluator.AccuracyMacro);
LogLoss = FetchDouble(MultiClassClassificationEvaluator.LogLoss);
LogLossReduction = FetchDouble(MultiClassClassificationEvaluator.LogLossReduction);
MicroAccuracy = FetchDouble(MulticlassClassificationEvaluator.AccuracyMicro);
MacroAccuracy = FetchDouble(MulticlassClassificationEvaluator.AccuracyMacro);
LogLoss = FetchDouble(MulticlassClassificationEvaluator.LogLoss);
LogLossReduction = FetchDouble(MulticlassClassificationEvaluator.LogLossReduction);
TopK = topK;
if (topK > 0)
TopKAccuracy = FetchDouble(MultiClassClassificationEvaluator.TopKAccuracy);
TopKAccuracy = FetchDouble(MulticlassClassificationEvaluator.TopKAccuracy);

var perClassLogLoss = RowCursorUtils.Fetch<VBuffer<double>>(ectx, overallResult, MultiClassClassificationEvaluator.PerClassLogLoss);
var perClassLogLoss = RowCursorUtils.Fetch<VBuffer<double>>(ectx, overallResult, MulticlassClassificationEvaluator.PerClassLogLoss);
PerClassLogLoss = perClassLogLoss.DenseValues().ToImmutableArray();
}

internal MultiClassClassificationMetrics(double accuracyMicro, double accuracyMacro, double logLoss, double logLossReduction,
internal MulticlassClassificationMetrics(double accuracyMicro, double accuracyMacro, double logLoss, double logLossReduction,
int topK, double topKAccuracy, double[] perClassLogLoss)
{
MicroAccuracy = accuracyMicro;
Loading