Dynamic learning technique allows the user to train a model in batch wise manner
Use the package manager pip to install Exchange Rate Api
pip install Dynamic-Learning-Technique
The DLT takes 2 argument with 6 optional arguments
# Initialize an object to DLT
from DLT import *
from sklearn.tree import DecisionTreeRegressor
import asyncio
async def main():
obj = DLT(['X dataset'], ['Y dataset'], DecisionTreeRegressor())
await obj.start()
if __name__ == "__main__":
asyncio.run(main())
-
New supported algorithms has been included
- RandomForestClassifier
- DecisionTreeClassifier
- SVC
- RandomForestRegressor
- DecisionTreeRegressor
- LinearRegression
- LogisticRegression
- SVR
- Ridge
- Lasso
-
New exceptions has been included
- NoArgumentException
- InvalidMachineLearningModel
- InvalidDatasetProvided
- BatchCountGreaterThanBatchSize
-
- The splitting process has been made an asynchronous process in order to increase the speed of the splitting process
Test cases has been included
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.