Practice #educational #easy #regression

TMPMN

Hidden

Predict Mean Temperature

AIcrowd

1304

🛠 Contribute: Found a typo? Or any other change in the description that you would like to see? Please consider sending us a pull request in the public repo of the challenge here.

🕵️ Introduction

Up for a magic trick? Want us to conjure a challenge out of thin air? Well this time we may just have done that, literally!, Feel the magic in the air.

Given some non-temperature based information for weather conditions on a given day, can you predict the mean temperature ?

Understand with code! Here is getting started code for you.😄

💾 Dataset

This data contains the weather information of Izmir region from 01/01/1994 to 31/12/1997. From given features, the goal is to predict the mean temperature. There will be 9 attributes that shall be provided to you and you are required to predict the mean temperature.

The 9 attributes are :

Max_temperature: range[36.7,105.0]
Min_temperature: range[15.8,78.6]
Dewpoint: range[13.6,64.4]
Precipitation: range[0.0,7.6]
Sea_level_pressure: range[29.26,30.48]
Standard_pressure: range[2.3,10.1]
Visibility: range[0.92,29.1]
Wind_speed: range[4.72,68.8]
Max_wind_speed: range[16.11,55.24]
Mean_temperature: range[29.4,89.9] [target]

For simplification, attributes have been stored in the CSV file. The train.csv has 10 columns, the last column is the mean_temp.

📁 Files

Following files are available in the resources section:

train.csv - (1168 samples) This csv file contains the attributes describing an day conditions of the place along with the mean temperature.
test.csv - (293 samples) File that will be used for actual evaluation for the leaderboard score but does not have the value of the mean temperature.

🚀 Submission

Prepare a CSV containing header as mean_temp and predicted values of the mean temperatures.
Name of the above file should be submission.csv.
Sample submission format is available in the resources section of the challenge page as sample_submission.csv.

Make your first submission here 🚀 !!