论文标题
决策树J48在Semeval-2020任务9：代码混合社交媒体文本（Hinglish）的情感分析
Decision Tree J48 at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text (Hinglish)
论文作者
论文摘要
本文讨论了用于为Semeval-2020任务9提供的问题提供解决方案的系统的设计，其中需要执行代码混合语言的情感分析和英语。该系统使用WEKA用作提供分类器进行分类的工具，而Python用于从提供的文件中加载数据并清洁。仅向系统提供了一部分培训数据，以对进行系统评估的测试数据集中的推文进行分类。使用官方竞争评估度量得分评估系统性能。分类器接受了两组训练数据的培训，该数据的F1得分为0.4972和0.5316。
This paper discusses the design of the system used for providing a solution for the problem given at SemEval-2020 Task 9 where sentiment analysis of code-mixed language Hindi and English needed to be performed. This system uses Weka as a tool for providing the classifier for the classification of tweets and python is used for loading the data from the files provided and cleaning it. Only part of the training data was provided to the system for classifying the tweets in the test data set on which evaluation of the system was done. The system performance was assessed using the official competition evaluation metric F1-score. Classifier was trained on two sets of training data which resulted in F1 scores of 0.4972 and 0.5316.
