An integrated machine learning analysis framework
Project description
xeasy-ml
1. What is xeasy-ml
Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly bui -ld a machine learning model and use the model to process and analyze his own data. At the same time, we have also realized the automatic analysis of data. During data proces -sing, xeasy-ml will automatically draw data box plots, distribution histograms, etc., and perform feature correlation analysis to help users quickly discover the value of data.
2.Installation
Dependencies
xeasy-ml requires:
Scikit-learn >= 0.24.1
Pandas >= 0.24.2
Numppy >= 1.19.5
Matplotlib >= 3.3.4
Pydotplus >= 2.0.2
Xgboost >= 1.4.2
User installation
pip install xeasy-ml
3. Quick Start
1.Create a new project
Create a new python file named pro_init.py to initialize the project.
from xeasy_ml.project_init.create_new_demo import create_project
import os
pro_path = os.getcwd()
create_project(pro_path)
Now you can see the following file structure in your project.
├── Your_project
...
│ ├── pro_init.py
│ ├── project
│ │ └── your_project
2.Run example
cd project/your_project
python __main__.py
3.View Results
cd project/your_project_name/result/v1
ls -l
├── box (Box plot)
├── cross_predict.txt (Cross-validation prediction file)
├── cross.txt (Cross validation effect evaluation)
├── deleted_feature.txt (Features that need to be deleted)
├── demo_feature_weight.txt (Feature weights)
├── demo.m (Model)
├── feature_with_feature (Feature similarity)
├── feature_with_label (Similarity between feature and label )
├── hist (Distribution histogram)
├── model
├── predict_result.txt (Test set prediction results)
└── test_score.txt (Score on the test set)
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