Automatic Model Selection

• AMPL: The ATOM Modeling PipeLine (AMPL) is an open-source, modular, extensible software pipeline for building and sharing models to advance in silico drug discovery, extending the functionality of DeepChem and supporting an array of machine learning and molecular featurization tools.
  
• CHVS: This repository contains Python code for model evaluation in regression tasks, exploring various regression models and helping select the best-performing model for your dataset using PCA and Mutual Information for feature selection.
  
• PREFER: The PREFER framework automates the evaluation of different combinations of molecular representations and machine learning models for predicting molecular properties, utilizing AutoSklearn for model selection and hyperparameter tuning.
  
• ROBERT: ROBERT: Bridging the Gap between Machine Learning and Chemistry
  
• SPOC: An integrated Python package for molecular descriptor generation, data processing, model training, and hyper-parameter optimization, aimed at facilitating the development of predictive models in the field of cheminformatics.
  
• TDC: