Data Science: Predict Damage Costs of Weather Events

Versione 1.0.4 (40,2 MB) da 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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2,7K download
Aggiornato 21 mag 2021
Visualizza la licenza su GitHub
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.

Cita come

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

Compatibilità della release di MATLAB
Creato con R2019a
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux
Categorie
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Le versioni che utilizzano il ramo predefinito di GitHub non possono essere scaricate

Versione Pubblicato Note della release
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

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.