Download Model

How to download model?

You can click the “Download model” button of the corresponding task in the “operation” column to download the trained ML model. As shown below:

Model File Structure

You will get a compressed file named model_*.zip after downloading the model file, which records all information about the model and related metadata.

 

You will extract a folder named “result” using a decompression tool, as shown in the following figure:

The folder can be roughly divided into the following parts:

 

l  example.py files：These files are code samples of ML model usage generated by our platform, including use for new data predictions, or reproduce model without our platform.

 

l  result folder：This folder stores metadata and other relevant files in the model training process, including AutoFE, AutoML, and modeling task configuration files.

 

These code requires our library called “changtianml” in the Python public warehouse PyPI , through which the dependency library can be more portable and convenient for users. You can easily do your own magic with ML models, make integrations to your own applications and more starting with downloaded models.

 

At present, the tool library is still in continuous iteration and improvement, keep updated to know new features!

Model Metadata

Modeling Task Configuration

The configuration information and advanced parameters involved in this modeling process are stored in the config.yaml file.

AutoFE

File Name	Description
features.csv	Advanced feature list (Latex formula style)）
record.csv	Advanced feature list details (CSV format)
result	Advanced feature list details (JSON format)
labelencoder.pkl	Automated feature engineering model binaries
dfs_log	autoFE log

AutoML

File Name	Description
result	autoML binaries
val_res	Validation set prediction result file
val_logs	Validation set evaluation metrics file
logs	autoML logs