metadata

license: mit
library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_file: HME_pickle
widget:
  structuredData:
    anger:
      - 0.13340177
      - 0.26429585
      - 0.75805366
    disgust:
      - 0.07661828
      - 0.14570697
      - 0.21044387
    fear:
      - 0.094705686
      - 0.057977196
      - 0.003689876
    joy:
      - 0.006762238
      - 0.2627153
      - 0.001755206
    neutral:
      - 0.03295978
      - 0.019884355
      - 0.013996695
    sadness:
      - 0.6507381
      - 0.24445744
      - 0.011482558
    surprise:
      - 0.004814104
      - 0.00496282
      - 0.000578273

Model description

[More Information Needed]

Intended uses & limitations

[More Information Needed]

Training Procedure

Hyperparameters

The model is trained with below hyperparameters.

Click to expand

Hyperparameter	Value
alpha	1
class_prior
fit_prior	1
norm	0

Model Plot

The model plot is below.

ComplementNB()

Please rerun this cell to show the HTML repr or trust the notebook.

Evaluation Results

You can find the details about evaluation process and the evaluation results.

Metric	Value
accuracy	0.536424
f1 score	0.536424

How to Get Started with the Model

[More Information Needed]

Model Card Authors

This model card is written by following authors:

[More Information Needed]

Model Card Contact

You can contact the model card authors through following channels: [More Information Needed]

Citation

Below you can find information related to citation.

BibTeX:

[More Information Needed]

citation_bibtex

bibtex @inproceedings{...,year={2022}}

model_card_authors

skops_user

limitations

This model is purely for academic purposes.

model_description

This is a Complement NB model trained on a poetry dataset.

eval_method

The model is evaluated using test split, on accuracy and F1 score with macro average.