Comparative study of xai using formal concept lattice and lime (Record no. 19044)

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control field 20230327095303.0
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fixed length control field 230327b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency AIKTC-KRRC
Transcribing agency AIKTC-KRRC
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 20276
Author Venkatsubramaniam, Bhaskaran
245 ## - TITLE STATEMENT
Title Comparative study of xai using formal concept lattice and lime
250 ## - EDITION STATEMENT
Volume, Issue number Vol.13(1), Oct
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Chennai
Name of publisher, distributor, etc. ICT Academy
Year 2022
300 ## - PHYSICAL DESCRIPTION
Pagination 2782-2791p.
520 ## - SUMMARY, ETC.
Summary, etc. Local Interpretable Model Agnostic Explanation (LIME) is a<br/>technique to explain a black box machine learning model using a<br/>surrogate model approach. While this technique is very popular,<br/>inherent to its approach, explanations are generated from the surrogate<br/>model and not directly from the black box model. In sensitive domains<br/>like healthcare, this need not be acceptable as trustworthy. These<br/>techniques also assume that features are independent and provide<br/>feature weights of the surrogate linear model as feature importance. In<br/>real life datasets, features may be dependent and a combination of a set<br/>of features with their specific values can be the deciding factor rather<br/>than individual feature importance. They also generate random<br/>instances around the point of interest to fit the surrogate model. These<br/>random instances need not be part of the original source or may even<br/>turn out to be meaningless. In this work, we compare LIME to<br/>explanations from the formal concept lattice. This does not use a<br/>surrogate model but a deterministic approach by generating synthetic<br/>data that respects implications in the original dataset and not randomly<br/>generating it. It obtains crucial feature combinations with their values<br/>as decision factors without presuming dependence or independence of<br/>features. Its explanations not only cover the point of interest but also<br/>global explanation of the model, similar and contrastive examples<br/>around the point of interest. The explanations are textual and hence<br/>easier to comprehend than comprehending weights of a surrogate<br/>linear model to understand the black box model.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 4622
Topical term or geographic name entry element Computer Engineering
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 20277
Co-Author Baruah, Pallav Kumar
773 0# - HOST ITEM ENTRY
Place, publisher, and date of publication Chennai ICT Academy
Title ICTACT Journal on Soft Computing (IJSC)
856 ## - ELECTRONIC LOCATION AND ACCESS
URL https://ictactjournals.in/paper/IJSC_Vol_13_Iss_1_Paper_6_2782_2791.pdf
Link text Click here
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
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    Dewey Decimal Classification     School of Engineering & Technology School of Engineering & Technology Archieval Section 27/03/2023   2023-0515 27/03/2023 27/03/2023 Articles Abstract Database
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