EngrSamad/Titanic-Survival-Predictor

Model description

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Intended uses & limitations

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Training Procedure

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Hyperparameters

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Hyperparameter	Value
C	1.0
class_weight
dual	False
fit_intercept	True
intercept_scaling	1
l1_ratio
max_iter	100
multi_class	auto
n_jobs
penalty	l2
random_state
solver	lbfgs
tol	0.0001
verbose	0
warm_start	False

Model Plot

LogisticRegression()

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Evaluation Results

Metric	Value
accuracy	0.728814
f1 score	0.728814

How to Get Started with the Model

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Model Card Authors

This model card is written by following authors:

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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:

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citation_bibtex

bibtex @inproceedings{...,year={2024}}

get_started_code

import pickle with open(dtc_pkl_filename, 'rb') as file: clf = pickle.load(file)

model_card_authors

skops_user

limitations

This model is ready to be used to production in titanic dataset.

model_description

This is a LogisticRegression model trained on titanic dataset.

eval_method

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

confusion_matrix