kulkarni-vishwanath / ML_For_Agriculture_AV_Hackathon

This repository contains the code for ML For Agriculture Hackathon hosted by Analytics Vidhya.

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Janatahack: Machine Learning in Agriculture

The Toxic Pesticides

Though, many of us don't appreciate much, but a farmer's job is real test of endurance and determination. Once the seeds are sown, he works days and nights to make sure that he cultivates a good harvest at the end of season. A good harvest is ensured by several factors such as availability of water, soil fertility, protecting crops from rodents, timely use of pesticides & other useful chemicals and nature. While a lot of these factors are difficult to control for, the amount and frequency of pesticides is something the farmer can control.

Pesticides are also special, because while they protect the crop with the right dosage. But, if you add more than required, they may spoil the entire harvest. A high level of pesticide can deem the crop dead / unsuitable for consumption among many outcomes. This data is based on crops harvested by various farmers at the end of harvest season. To simplify the problem, you can assume that all other factors like variations in farming techniques have been controlled for.

You need to daetermine the outcome of the harvest season, i.e. whether the crop would be healthy (alive), damaged by pesticides or damaged by other reasons.

Data Description

Variable Description
ID Unique ID
Estimated_Insects_Count Estimated insects count per square meter
Crop_Type Category of Crop(0,1)
Soil_Type Category of Soil (0,1)
Pesticide_Use_Category Type of pesticides uses (1- Never, 2-Previously Used, 3-Currently Using)
Number_Doses_Week Number of doses per week
Number_Weeks_Used Number of weeks used
Number_Weeks_Quit Number of weeks quit
Season Season Category (1,2,3)
Crop_Damage Crop Damage Category (0=alive, 1=Damage due to other causes, 2=Damage due to Pesticides)

Evaluation Metric

The evaluation metrics for this competition is Accuracy.

Leaderboard

Public Leaderboard: 49/574

Private Leaderboard: 49/574

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This repository contains the code for ML For Agriculture Hackathon hosted by Analytics Vidhya.


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