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Independent testing of ANN model trained on encoded datasets.

Domain:

healthcare

Record type:

dataset
Creator:
MasSamNicFre
Host:avatar

A) Applying an ANN model trained on the Encoded-Muleba-GA dataset to estimate the parity status of mosquitoes in the autoencoded Burkina-GA dataset. B) Applying the ANN model trained on the Encoded-Burkina-GA dataset to estimate the parity status of mosquitoes in the Encoded-Muleba-GA dataset.

Visit

figshare.com

Tags

MedicineNeuroscienceBiotechnologyCancerScience PolicyComputational BiologyBiological Sciences not elsewhere classifiedBurkina FasoNIRSspectra feature dimensions+9

Licenses

CC BY 4.0

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Training and testing of ANN model on autoencoded spectra.Training and testing ANN model on spectra preprocessed according to Mayagaya et al. [9].Box plots of parity estimation score when ANN models trained on 75% of spectra before the autoencoder was applied and tested on the remaining spectra (25%) (out of the sample testing).Artificially Fluent: Swahili AI Performance Benchmarks Between English-Trained and Natively-Trained DatasetsPerformance comparison of dense retrieval models trained on WebFAQ versus Wikipedia-based datasets for low-resource languagePre-trained Model Sentiment Analysis of Tunisian Telecommunications Operators’ Comments on Social Media

Training and testing of ANN model on autoencoded spectra.

M is either Minepa-ARA, Muleba-GA, Burkina-GA, or Muleba-Burkina-GA dataset.

Training and testing ANN model on spectra preprocessed according to Mayagaya et al. [9].

“M” is either Minepa-ARA, Muleba-GA, Burkina-GA, or Muleba-Burkina-GA.

Box plots of parity estimation score when ANN models trained on 75% of spectra before the autoencoder was applied and tested on the remaining spectra (25%) (out of the sample testing).

A, B, C, and D represent results for the Minepa-ARA, Muleba-GA, Burkina-GA, and Muleba-Burkina-GA

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