Automated Machine Learning Overview

Roman Budjac, Marcel Nikmon, Peter Schreiber, B. Zahradnikova, Dagmar Janáčová
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引用次数: 1

Abstract

Abstract This paper aims at deeper exploration of the new field named auto-machine learning, as it shows promising results in specific machine learning tasks e.g. image classification. The following article is about to summarize the most successful approaches now available in the A.I. community. The automated machine learning method is very briefly described here, but the concept of automated task solving seems to be very promising, since it can significantly reduce expertise level of a person developing the machine learning model. We used Auto-Keras to find the best architecture on several datasets, and demonstrated several automated machine learning features, as well as discussed the issue deeper.
自动化机器学习概述
本文旨在深入探索自动机器学习这一新领域,因为它在特定的机器学习任务(如图像分类)中显示出有希望的结果。下面的文章将总结目前人工智能社区中最成功的方法。这里非常简单地描述了自动机器学习方法,但自动任务解决的概念似乎非常有前途,因为它可以显着降低开发机器学习模型的人的专业水平。我们使用Auto-Keras在几个数据集上找到了最佳架构,并演示了几个自动机器学习功能,并对这个问题进行了更深入的讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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