ModelOperationsCatalog.CreatePredictionEngine Method
Definition
Important
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Overloads
| CreatePredictionEngine<TSrc,TDst>(ITransformer, DataViewSchema) |
Create a prediction engine for one-time prediction. It's mainly used in conjunction with Load(Stream, DataViewSchema), where input schema is extracted during loading the model. |
| CreatePredictionEngine<TSrc,TDst>(ITransformer, PredictionEngineOptions) |
Create a prediction engine for one-time prediction. It's mainly used in conjunction with Load(Stream, DataViewSchema), where input schema is extracted during loading the model. |
| CreatePredictionEngine<TSrc,TDst>(ITransformer, Boolean, SchemaDefinition, SchemaDefinition) |
Create a prediction engine for one-time prediction (default usage). |
CreatePredictionEngine<TSrc,TDst>(ITransformer, DataViewSchema)
Create a prediction engine for one-time prediction. It's mainly used in conjunction with Load(Stream, DataViewSchema), where input schema is extracted during loading the model.
public Microsoft.ML.PredictionEngine<TSrc,TDst> CreatePredictionEngine<TSrc,TDst> (Microsoft.ML.ITransformer transformer, Microsoft.ML.DataViewSchema inputSchema) where TSrc : class where TDst : class, new();member this.CreatePredictionEngine : Microsoft.ML.ITransformer * Microsoft.ML.DataViewSchema -> Microsoft.ML.PredictionEngine<'Src, 'Dst (requires 'Src : null and 'Dst : null and 'Dst : (new : unit -> 'Dst))> (requires 'Src : null and 'Dst : null and 'Dst : (new : unit -> 'Dst))Public Function CreatePredictionEngine(Of TSrc As Class, TDst As Class) (transformer As ITransformer, inputSchema As DataViewSchema) As PredictionEngine(Of TSrc, TDst)Type Parameters
- TSrc
The class that defines the input data.
- TDst
The class that defines the output data.
Parameters
- transformer
- ITransformer
The transformer to use for prediction.
- inputSchema
- DataViewSchema
Input schema.
Returns
Applies to
CreatePredictionEngine<TSrc,TDst>(ITransformer, PredictionEngineOptions)
Create a prediction engine for one-time prediction. It's mainly used in conjunction with Load(Stream, DataViewSchema), where input schema is extracted during loading the model.
public Microsoft.ML.PredictionEngine<TSrc,TDst> CreatePredictionEngine<TSrc,TDst> (Microsoft.ML.ITransformer transformer, Microsoft.ML.PredictionEngineOptions options) where TSrc : class where TDst : class, new();member this.CreatePredictionEngine : Microsoft.ML.ITransformer * Microsoft.ML.PredictionEngineOptions -> Microsoft.ML.PredictionEngine<'Src, 'Dst (requires 'Src : null and 'Dst : null and 'Dst : (new : unit -> 'Dst))> (requires 'Src : null and 'Dst : null and 'Dst : (new : unit -> 'Dst))Public Function CreatePredictionEngine(Of TSrc As Class, TDst As Class) (transformer As ITransformer, options As PredictionEngineOptions) As PredictionEngine(Of TSrc, TDst)Type Parameters
- TSrc
The class that defines the input data.
- TDst
The class that defines the output data.
Parameters
- transformer
- ITransformer
The transformer to use for prediction.
- options
- PredictionEngineOptions
Advanced configuration options.
Returns
Applies to
CreatePredictionEngine<TSrc,TDst>(ITransformer, Boolean, SchemaDefinition, SchemaDefinition)
Create a prediction engine for one-time prediction (default usage).
public Microsoft.ML.PredictionEngine<TSrc,TDst> CreatePredictionEngine<TSrc,TDst> (Microsoft.ML.ITransformer transformer, bool ignoreMissingColumns = true, Microsoft.ML.Data.SchemaDefinition inputSchemaDefinition = default, Microsoft.ML.Data.SchemaDefinition outputSchemaDefinition = default) where TSrc : class where TDst : class, new();member this.CreatePredictionEngine : Microsoft.ML.ITransformer * bool * Microsoft.ML.Data.SchemaDefinition * Microsoft.ML.Data.SchemaDefinition -> Microsoft.ML.PredictionEngine<'Src, 'Dst (requires 'Src : null and 'Dst : null and 'Dst : (new : unit -> 'Dst))> (requires 'Src : null and 'Dst : null and 'Dst : (new : unit -> 'Dst))Public Function CreatePredictionEngine(Of TSrc As Class, TDst As Class) (transformer As ITransformer, Optional ignoreMissingColumns As Boolean = true, Optional inputSchemaDefinition As SchemaDefinition = Nothing, Optional outputSchemaDefinition As SchemaDefinition = Nothing) As PredictionEngine(Of TSrc, TDst)Type Parameters
- TSrc
The class that defines the input data.
- TDst
The class that defines the output data.
Parameters
- transformer
- ITransformer
The transformer to use for prediction.
- ignoreMissingColumns
- Boolean
Whether to throw an exception if a column exists in
outputSchemaDefinition but the corresponding member doesn't exist in
TDst.
- inputSchemaDefinition
- SchemaDefinition
Additional settings of the input schema.
- outputSchemaDefinition
- SchemaDefinition
Additional settings of the output schema.
Returns
Examples
using System;
using System.Collections.Generic;
using System.IO;
using Microsoft.ML;
namespace Samples.Dynamic.ModelOperations
{
public class SaveLoadModel
{
public static void Example()
{
// Create a new ML context, for ML.NET operations. It can be used for
// exception tracking and logging, as well as the source of randomness.
var mlContext = new MLContext();
// Generate sample data.
var data = new List<Data>()
{
new Data() { Value="abc" }
};
// Convert data to IDataView.
var dataView = mlContext.Data.LoadFromEnumerable(data);
var inputColumnName = nameof(Data.Value);
var outputColumnName = nameof(Transformation.Key);
// Transform.
ITransformer model = mlContext.Transforms.Conversion
.MapValueToKey(outputColumnName, inputColumnName).Fit(dataView);
// Save model.
mlContext.Model.Save(model, dataView.Schema, "model.zip");
// Load model.
using (var file = File.OpenRead("model.zip"))
model = mlContext.Model.Load(file, out DataViewSchema schema);
// Create a prediction engine from the model for feeding new data.
var engine = mlContext.Model
.CreatePredictionEngine<Data, Transformation>(model);
var transformation = engine.Predict(new Data() { Value = "abc" });
// Print transformation to console.
Console.WriteLine("Value: {0}\t Key:{1}", transformation.Value,
transformation.Key);
// Value: abc Key:1
}
private class Data
{
public string Value { get; set; }
}
private class Transformation
{
public string Value { get; set; }
public uint Key { get; set; }
}
}
}