ML-Project

ML-Project (Supervoised Learning)

🌱 Soil-Based Crop Prediction using Machine Learning

🏆 Single Feature Evaluation

We trained a separate Logistic Regression model for each feature (N, P, K, ph) to measure its individual ability to predict the crop.

📈 F1 Scores by Feature:

• Nitrogen (N): 0.09149868209906838
• Phosphorous (P): 0.14761942909728204
• Potassium (K): 0.23896974566001802
• pH: 0.04532731061152114

➡️ Result: The feature Potassium (K) achieved the highest F1 score, meaning it is the most important single feature for predicting the best crop to plant.

This insight helps farmers focus on measuring Potassium when testing resources are limited.