自动化探索性数据分析

UMT Artificial Intelligence Review Pub Date : 2021-12-31 DOI:10.32350/air.0102.04

Hubble Dhillon

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引用次数: 0

摘要

本研究引入了一个新的框架，可以推广到自动化探索性数据分析，以测试给定的假设。目前的工作是关于药物相关的趋势，也提供了一个特定的模型来测试COVID-19病例中与动机相关的假设。通过使用正确、适当和优化的解决方案来解决问题，用户会感到有动力深入研究解决方案以改善社会，这一点很重要。关键词:自动化探索性数据分析，动机相关假设

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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Automated Exploratory Data Analysis

This study introduces a novel framework that can be generalized for an automated exploratory data analysis to test a given hypothesis. The current work is about a drug-related trend and also provides a specific model to test a motivation-related hypothesis in the case of COVID-19. With the utilization of the right, appropriate, and optimized solution available to solve a problem, it is significant that the user feels motivated to delve into the solution for the betterment of society. KEYWORDS: automated exploratory data analysis, motivation-related hypothesis

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UMT Artificial Intelligence Review

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