Automated Machine Learning Framework for Data Analysis.
Project description
Automated Machine Learning Framework for Data Analysis
Key Features
- Automated Model Selection: The framework automatically selects the most suitable machine learning model based on the characteristics of the dataset.
- Feature Engineering: It automatically applies various feature engineering techniques to preprocess the data and enhance the predictive power of the models.
- Hyperparameter Optimization: The library performs hyperparameter optimization to fine-tune the models and improve their performance.
- Performance Evaluation: It provides comprehensive evaluation metrics to assess the performance of the models and compare different approaches.
Usage
- Make sure you have Python installed in your system.
- Run Following command in the Terminal.
pip install UAutoml
Example
# test.py
import UAutoml
## Make sure u have follwing paramters
dataset = '/Path'
Target = 'Column_Name'
(this are optional)
Hyper_optimazation: If needed set value to 1 or in default 0
epochs: IN default its 5 you can set your requirements
## To run
# To get full automated process
r = UAutoml.process_data(dataset,Target)
# To get the features data
features = UAutoml.feature(dataset,Target)
Run the following Script.
python test.py
Note
- I have tried to implement all the functionality, it might have some bugs also. Ignore that or please try to solve that bug.
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