Feature Importance plots for Subset-IGD_MS:

(a) Summary plot between SHAP feature importance values v/s 20 most important features illustrating SHAP feature importance values for Subset-IGD_MS data modality on CSMLP model, focusing on “Fruity” odor class. (b) SHAP Bar plot between Feature Index v...

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Bibliographic Details
Main Author:	Durgesh Ameta (21439753) (author)
Other Authors:	Surendra Kumar (33312) (author), Rishav Mishra (21439756) (author), Laxmidhar Behera (14341372) (author), Aniruddha Chakraborty (394000) (author), Tushar Sandhan (21439759) (author)
Published:	2025
Subjects:	Space Science Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified use machine learning systematic study compares sensitive model outperform selected representation method random resampling techniques proposed resampling techniques mld )&# 8212 deep learning approaches multimodal features obtained exploring feature performance based features compared direct comparative studies odor classification multi label classification models three mentioned features large novel dataset explainable model sheds molecular fingerprint features odor classification molecular fingerprint three kinds predictive performance label datasets different features recent studies previous studies molecular fingerprints xlink "> vibrational spectra usually represented two gaps sensory modality second objective research delves remains complex odour relations multifaceted approach inherent challenge inadequately understood inadequately documented fp ). first one electric nose data imbalance csmlp ). class imbalance also report
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Feature Importance plots for Subset-IGD_MS:

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