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A machine learning model that predicts the ideal crop based on a combination of soil elements, temperature, humidity, and rainfall data. The repository includes all relevant code, data sets, and documentation, as well as a detailed description of the model's methodology and performance metrics

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NouraAlgohary/Crop-Recommendation

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ML--Crop-Recommendation

A machine learning model to determine the best crop based on soil elements, temperature, humidity, and rainfall.

Data

Link to data

Atrributes

Input

  • N - ratio of Nitrogen (NH4+) content in soil
  • P - ratio of Phosphorous (P) content in soil
  • K - ratio of Potassium (K) content in soil
  • temperature
  • humidity
  • ph
  • rainfall

Target

  • Recommended crop

Limitations

Requirments

Requirments

Code

  1. Data Loading and Discovery
  2. Choose a Model:
    • Random Forest Classifier
    • GaussianNB
    • SVC
    • Logistic Regression
    • DecisionTreeClassifier
  3. Testing

Results

  • Train Accuracy = 100%
  • Test Accuracy = 99.3%

About

A machine learning model that predicts the ideal crop based on a combination of soil elements, temperature, humidity, and rainfall data. The repository includes all relevant code, data sets, and documentation, as well as a detailed description of the model's methodology and performance metrics

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