https://github.com/parinithshekar/rainfall-prediction

Rainfall prediction models (Linear and Logistic) trained on publicly available datasets from Austin, Texas
https://github.com/parinithshekar/rainfall-prediction

linear-regression logistic-regression matplotlib rainfall sklearn weather

Last synced: 5 months ago
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Rainfall prediction models (Linear and Logistic) trained on publicly available datasets from Austin, Texas

• Host: GitHub
• URL: https://github.com/parinithshekar/rainfall-prediction
• Owner: parinithshekar
• Created: 2018-07-06T09:04:42.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2018-07-06T09:38:29.000Z (almost 8 years ago)
• Last Synced: 2023-12-16T15:16:04.291Z (over 2 years ago)
• Topics: linear-regression, logistic-regression, matplotlib, rainfall, sklearn, weather
• Language: Python
• Homepage:
• Size: 79.1 KB
• Stars: 12
• Watchers: 2
• Forks: 12
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
This repository builds a Linear as well as a Logistic model to predict rainfalls in Austin, Texas.

The following dataset constitutes 3.5 years worth of weather data, including temperature, humidity, dewpoints, etc: https://www.kaggle.com/grubenm/austin-weather

Execute the files **linearRegression.py** and **logisticRegression.py** to obtain predictions for an arbitrary day with hardcoded input parameters.

![5b3f34740ce87](https://i.loli.net/2018/07/06/5b3f34740ce87.png)

A day (in red) having a precipitation of about 2 inches is tracked across multiple parameters.

![5b3f34511cde8](https://i.loli.net/2018/07/06/5b3f34511cde8.png)

Manually classifying the precipitation levels into 4 different classes as follows:

- No Rain: precipitation<0.001

- Drizzle: 0.001<=precipitation<0.1

- Moderate Rains: 0.1<=precipitation< 1.2

- Heavy Rains: precipitation>=1.2

The graphs we obtain after classifying express various trends which tie rainfall and humidity, visibility and temperature together.

![5b3f36bd69c75](https://i.loli.net/2018/07/06/5b3f36bd69c75.png)