This repository contains examples of MindsDB usage in predicting different types of data.
pip install mindsdb
or
pip install -r requirements.txt
In each directory there are different types of datasets avaiable.
cd home_rentals
python3 train.py
Inside dataset directory you can find dataset with Test data. e.g benchmarks/home_rentals/dataset/home_rentals_train.csv. You can use this dataset to check the prediction accuracy.
cd benchmarks/home_rentals
python3 mindsdb_acc.py
Lets make our predictions for which we will model the relationship between the three variables and rental price. e.g
Predictor(name='home_rentals').predict(when={'number_of_rooms': 3, 'number_of_bathrooms': 1, 'neighborhood' : 'south_side'})MindsDB will automatically predict a rental price cost value given number_of_rooms, number_of_bathrooms and neighborhood parameters, e.g
- We are 77% confident the value of "rental_price" lies between 4586 and 4960.
Check the following tutorial, to learn more about MindsDB end-to-end.
