xeasy-ml 0.1.3

An integrated machine learning analysis framework

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）