接收到，“抛出错误并没有捕获:提供的验证数据必须包含.”使用CreateML创建文本分类器模型时

Question

我正在使用Playground创建一个使用CreateML的文本分类器模型，并不断地获取错误：

Playground execution terminated: An error was thrown and was not caught:
▿ The validation data provided must contain class.
  ▿ type : 1 element
    - reason : "The validation data provided must contain class."

我的代码相对简单，使用了数据表中的两列。textColumn标记为"text“，labelColumn标记为"class"：

import Cocoa
import CreateML

let data = try MLDataTable(contentsOf: URL(fileURLWithPath: "/Users/ ... .csv"))
let(trainingData, testingData) = data.randomSplit(by: 0.8, seed: 5)
let sentimentClassifier = try MLTextClassifier(trainingData: trainingData, textColumn: "text", labelColumn: "class")
let evaluationMetrics = sentimentClassifier.evaluation(on: testingData, textColumn: "text", labelColumn: "class")
let evaluationAccuracy = (1.0 - evaluationMetrics.classificationError) * 100

我能找到的与Apple Developer文档中提供的代码之间唯一的区别是，而不是

let evaluationMetrics = sentimentClassifier.evaluation(on: testingData, textColumn: "text", labelColumn: "class")

他们的文件是：

let evaluationMetrics = sentimentClassifier.evaluation(on: testingData)

如果我尝试使用Apple Developer文档中的代码行，那么Xcode的11.2.1版本会给我一个失败。

提前感谢你能提供的任何帮助。

Answer 1

尝尝这个!对我来说很管用

let data = try MLDataTable(contentsOf: URL(fileURLWithPath: "/Users/justinmacbook/Desktop/twitter-sanders-apple3.csv"))

let (trainingData, testingData) = data.randomSplit(by: 0.8, seed: 5 )

let sentimentClassifier = try MLTextClassifier(trainingData: trainingData, textColumn: "class", labelColumn: "text")

let evaluationMetrics = sentimentClassifier.evaluation(on: testingData, textColumn: "class", labelColumn: "text")

let evaluationAccuracy = (1.0 - evaluationMetrics.classificationError) * 100

Answer 2

这是对我有效的解决方案。我相信这个原始代码只适用于OSX 10.15+。

import Cocoa
import CreateML
import NaturalLanguage

let data = try MLDataTable(contentsOf: URL(fileURLWithPath: "/Users/m0a04y6/Desktop/iOS/ML/twitter-sanders-apple3.csv"))

let (trainingData, testingData) = data.randomSplit(by: 0.8, seed: 5)
    
let parameters = MLTextClassifier.ModelParameters.init(validationData: trainingData, algorithm: MLTextClassifier.ModelAlgorithmType.maxEnt(revision: 1), language: NLLanguage.english, textColumnValidationData: "text", labelColumnValidationData: "class")
let sentimentClassifier = try MLTextClassifier(trainingData: trainingData, textColumn: "text", labelColumn: "class", parameters: parameters)

let evaluationMetrics = sentimentClassifier.evaluation(on: testingData, textColumn: "text", labelColumn: "class")     //Training accuracy as a percentage

let evaluationAccuracy = (1.0 - evaluationMetrics.classificationError) * 100
print(evaluationAccuracy)

let metadata = MLModelMetadata(author: "Madhur Ahuja", shortDescription: "A model trained to classify movie review sentiment", version: "1.0")
try sentimentClassifier.write(to: URL(fileURLWithPath: "/Users/m0a04y6/Desktop/iOS/ML/sentiment.mlmodel"), metadata: metadata)