MLModel lookup

Advanced

MLModel lookup 

Contains information about the selected data for the model, the training period, the current training status, etc.

Main MLModel lookup fields 

Name String

Model name.

ModelInstanceUId Unique identifier

The identifier of the current model instance.

TrainedOn Date/time

The date/time of last training attempt.

TriedToTrainOn Date/time

The date/time of last training attempt.

TrainFrequency Integer

Model retraining frequency (days).

MetaData String

Metadata with selection column types.

Metadata JSON format
{
    inputs: [
        {
            name: "Name of the field 1 in the data sample",
            type: "Text",
            isRequired: true
        },
        {
            name: "Name of the field 2 in the data sample",
            type: "Lookup"
        },
        //...
    ],
    output: {
        name: "Resulting field",
        type: "Lookup",
        displayName: "Name of the column to display"
    }
}

In this code:

  • inputs – a set of incoming columns for the model.
  • output – a column, the value of which the model should predict.

Column descriptions support the following attributes:

  • name – field name from the TrainingSetQuery expression.
  • type – data type for the training engine.
    Supported values
    Text text column;
    Lookup lookup column;
    Boolean logical data type;
    Numeric numeric type;
    DateTime date and time.
  • isRequired – mandatory field value (true/false). Default value – false.
TrainingSetQuery String

C#-expression of the training data selection. This expression should return the Terrasoft.Core.DB.Select class instance.

TrainingSetQuery example
(Select)new Select(userConnection)
.Column("Id")
.Column("Symptoms")
.Column("CreatedOn")
.From("Case", "c")
.OrderByDesc("c", "CreatedOn")
Attention. Select the “Unique identifier” column type in the selection expression. This column should have the Id name.
Attention. If the selection expression contains a column for sorting, then this column must be present in the resulting selection.

You can find examples of queries in the "Examples of data queries for the machine learning model” example.

RootSchemaUId Unique identifier

A link to an object schema for which the prediction will be executed.

Status String

The status of model processing (data transfer, training, ready for forecasting).

InstanceMetric Number

A quality metric for the current model instance.

MetricThreshold Number

Lowest threshold of model quality.

PredictionEnabled Logical

A flag that includes the prediction for this model.

TrainSessionId Unique identifier

Current training session.

MLProblemType Unique identifier

Machine learning problem (defines the algorithm and service url for model training).