Basic Weather Prediction Model
- This is A basic Weather Prediction Model which uses SVM to determine if it will rain or not.
- I have considered in parameters like Season, temperature, Humdiity, Cloudy or not.
- Load and prepare the dataset using pandas.
- Visualize the data with seaborn to get an understanding of patterns.
- Preprocess the data: Use LabelEncoder for categorical variables.
- Scale numerical data(like Temperature, Humidity, WindSpeed) using MinMaxScaler.
- Split the dataset into training and testing using train_test_split, 80% to 20% ratio
- Train the model using SVM.
- Evaluate the model using classification_report to assess its performance.
precision recall f1-score support
0 1.00 0.33 0.50 3
1 0.00 0.00 0.00 0
accuracy 0.33 3
macro avg 0.50 0.17 0.25 3 weighted avg 1.00 0.33 0.50 3