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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
@file:Suppress("NAME_SHADOWING", "DEPRECATION")
package com.pulumi.azurenative.machinelearningservices.kotlin.outputs
import kotlin.String
import kotlin.Suppress
/**
* Text Classification task in AutoML NLP vertical.
* NLP - Natural Language Processing.
* @property featurizationSettings Featurization inputs needed for AutoML job.
* @property limitSettings Execution constraints for AutoMLJob.
* @property logVerbosity Log verbosity for the job.
* @property primaryMetric Primary metric for Text-Classification task.
* @property targetColumnName Target column name: This is prediction values column.
* Also known as label column name in context of classification tasks.
* @property taskType AutoMLJob Task type.
* Expected value is 'TextClassification'.
* @property trainingData [Required] Training data input.
* @property validationData Validation data inputs.
*/
public data class TextClassificationResponse(
public val featurizationSettings: NlpVerticalFeaturizationSettingsResponse? = null,
public val limitSettings: NlpVerticalLimitSettingsResponse? = null,
public val logVerbosity: String? = null,
public val primaryMetric: String? = null,
public val targetColumnName: String? = null,
public val taskType: String,
public val trainingData: MLTableJobInputResponse,
public val validationData: MLTableJobInputResponse? = null,
) {
public companion object {
public fun toKotlin(javaType: com.pulumi.azurenative.machinelearningservices.outputs.TextClassificationResponse): TextClassificationResponse = TextClassificationResponse(
featurizationSettings = javaType.featurizationSettings().map({ args0 ->
args0.let({ args0 ->
com.pulumi.azurenative.machinelearningservices.kotlin.outputs.NlpVerticalFeaturizationSettingsResponse.Companion.toKotlin(args0)
})
}).orElse(null),
limitSettings = javaType.limitSettings().map({ args0 ->
args0.let({ args0 ->
com.pulumi.azurenative.machinelearningservices.kotlin.outputs.NlpVerticalLimitSettingsResponse.Companion.toKotlin(args0)
})
}).orElse(null),
logVerbosity = javaType.logVerbosity().map({ args0 -> args0 }).orElse(null),
primaryMetric = javaType.primaryMetric().map({ args0 -> args0 }).orElse(null),
targetColumnName = javaType.targetColumnName().map({ args0 -> args0 }).orElse(null),
taskType = javaType.taskType(),
trainingData = javaType.trainingData().let({ args0 ->
com.pulumi.azurenative.machinelearningservices.kotlin.outputs.MLTableJobInputResponse.Companion.toKotlin(args0)
}),
validationData = javaType.validationData().map({ args0 ->
args0.let({ args0 ->
com.pulumi.azurenative.machinelearningservices.kotlin.outputs.MLTableJobInputResponse.Companion.toKotlin(args0)
})
}).orElse(null),
)
}
}
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