Data Science: Predict Damage Costs of Weather Events

版本 1.0.4 (40.2 MB) 作者: Heather Gorr, PhD
Explore data and use machine learning to predict the damage costs of storm events based on location, time of year, and type of event
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更新时间 2021/5/21
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The goal of this case study is to explore storm events in various locations in the United States and analyze the frequency and damage costs associated with different types of events. A machine learning model is used to predict the damage costs, based on historical data from 1980 - 2020. The calculations are then performed in an app, which can be shared as a web application.
This example also highlights techniques for cleaning data in various forms (numeric, text, categorical, dates and times) and working with large data sets which do not fit into memory.
The example is used in the "Data Science with MATLAB" webinar series.

引用格式

Heather Gorr, PhD (2024). Data Science: Predict Damage Costs of Weather Events (https://github.com/mathworks/data-science-predict-weather-events), GitHub. 检索时间: .

MATLAB 版本兼容性
创建方式 R2019a
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版本 已发布 发行说明
1.0.4

Included examples for Intro to MATLAB webinar
1.0.3

Link to GitHub
1.0.2

Included recent data, updated scripts to include Live Editor Tasks for data cleaning (available in R2019b)
1.0.1

Updated for Data Science w/ MATLAB webinar
1.0.0

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。
要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。