METHOD AND SYSTEM FOR EXPLAINABLE MACHINE LEARNING USING DATA AND PROXY MODEL BASED HYBRID APPROACH

    公开(公告)号:US20220374769A1

    公开(公告)日:2022-11-24

    申请号:US17663240

    申请日:2022-05-13

    Abstract: Conventionally three main approaches are utilized for explainability of blackbox ML systems: proxy or shadow model approaches, model inspection approaches and data based approaches. Most of the research work on explainability has followed one of the above approaches with each having its own limitations and advantages. Embodiments of the present disclosure provide a method and system for explainable Machine learning (ML) using data and proxy model based hybrid approach to explain outcomes of a ML model. The hybrid approach is based on Local Interpretable Model-agnostic Explanations (LIME) using Formal Concept Analysis (FCA) for structured sampling of instances. The approach combines the benefits of using a data-based approach (FCA) and proxy model-based approach (LIME).

    METHOD AND SYSTEM FOR GENERATING A RESPONSE TO AN UNSTRUCTURED NATURAL LANGUAGE (NL) QUERY

    公开(公告)号:US20220342919A1

    公开(公告)日:2022-10-27

    申请号:US17753514

    申请日:2020-03-04

    Abstract: For various applications (for example, a Virtual Assistant), mechanisms that are capable of collecting user queries and generating responses are being used. While such systems handle structured queries well, they struggle to or fail to interpret an unstructured Natural Language (NL) query. The disclosure herein generally relates to data processing, and, more particularly, to a method and a system for generating responses to unstructured Natural Language (NL) queries. The system collects at least one NL query as input at a time, and generates a sketch, where the sketch is a structured representation of the unstructured NL query. Further by processing the sketch, the system generates one or more database queries. The one or more database queries are then used to search in one or more associated databases and to retrieve matching results, which are then used to generate response to the at least one NL query.

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