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Trained Random Forest Model and Scaler Parameters for (Phy+Man), 15 August, 2024

Authors: Kharita, Akash;

Trained Random Forest Model and Scaler Parameters for (Phy+Man), 15 August, 2024

Abstract

This repository contains the trained models and scaler parameters. There are two trained random forest models. These models were trained on 5000 traces/class, The traces were of 40s (P-10, P+30), 110s (P-10, P+100) and 150s (P-50, P+100) bandpass filtered between 0.5-15 Hz, and resampled to 50 Hz. One of the models were trained on (Physical+Manual) features while other was trained on top 20 most important physical+manual features. 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average