Automates machine learning model construction for materials science via NJmatML. Please check https://github.com/Zhang-NJ-Lab/NJmatML-Functions/blob/main/define.ipynb
Project description
定义了一些函数用于机器学习建模. The test dataset is photocurrent voltages for surface modified halide perovksite films in water (or formation energy). file_name('train1.csv') hist() heatmap_before() feature_select(23,0) #第一个为剩的特征个数,第二个一般都为0 heatmap_afterRFE() FeatureImportance_before(80,8,10,4) #rotation=80, fontsize=8, figure_size_xaxis=10,figure_size_yaxis=4 FeatureImportance_afterRFE(80,12,5,4) #rotation=80, fontsize=12, figure_size_xaxis=5,figure_size_yaxis=4 xgboost_default() xgboost_modify(1000,200,0.2,0,0.9,0.8,0.2)
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
File details
Details for the file NJmatML-0.0.5-py3-none-any.whl
.
File metadata
- Download URL: NJmatML-0.0.5-py3-none-any.whl
- Upload date:
- Size: 11.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.8.8
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | dc148abe9d5a53b877b3c39781dd991f53209b989e690f9af33ac60cc75b8bed |
|
MD5 | ac3717851773200c9b6218d9102cf9f3 |
|
BLAKE2b-256 | eedca7650bfdc422c3e64a8fea73469f77206baff9b87679ab950ced3dc9be4e |