Active learning model validation

Abstract

Method(s), apparatus, and computer-implemented method(s) are provided for training a machine learning (ML) technique to generate a property model for predicting whether a compound has a particular property. An iterative procedure / feedback loop may be performed for generating the property model, the procedure including: generating a prediction result list for a plurality of compounds and their association with the particular property based on the property model; validating the property model based on compounds from the prediction result list having an association with the particular property; and updating the property model based on the property model validation. The procedure / loop may be repeated using the updated property model until it is determined the property model has been validly trained. The property model validation may include selecting a shortlist of compounds, performing simulation analysis and / or laboratory analysis on the shortlist of compounds in relation to the particular property and using the simulation and / or laboratory results in updating the property model.

Description

technical field [0001] The present application relates to devices, systems and methods for active learning and model validation. Background technique [0002] Informatics is the application of computer and information technology and resources to interpret data in one or more academic and / or scientific fields. Cheminformatics (also known as chem(o)informatics) and bioinformatics include the application of computer and information technology and resources to interpret chemical and / or biological data. This can include solving and / or Modeling processes and / or problems in the fields of chemistry and / or biology. For example, these computing and information technologies and resources can convert data into information, and then convert information into , knowledge in the field of discovery and optimization for rapid generation of compounds and / or improved decisions. [0003] Machine learning techniques are computational methods that can be used to design complex analytical models ...

AI Technical Summary

Problems solved by technology

Although a myriad of ML techniques can be used or chosen to predict whether a compound has a particular property or characteristic, there is often a lack of training data to properly train the ML technique to generate a suitable trained property model (referred to herein as a property model) to predict a compound Is there a specific characteristic

If ML techniques are used to generate property models based on insufficiently labeled training data, the resulting property models may not reliably predict whether a compound has a specific property for a broad range of compounds

[0004] Generating labeled training datasets used to train ML techniques to generate accurate and reliable property models to predict whether a compound has a specific property is expensive, time-consuming and prone to error due to human error

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