metadata

library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: NYC_SQF_ARR_SVM.pkl
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Model description

[More Information Needed]

Intended uses & limitations

[More Information Needed]

Training Procedure

[More Information Needed]

Hyperparameters

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Hyperparameter	Value
memory
steps	[('scaler', StandardScaler()), ('svm', SGDClassifier())]
verbose	False
scaler	StandardScaler()
svm	SGDClassifier()
scaler__copy	True
scaler__with_mean	True
scaler__with_std	True
svm__alpha	0.0001
svm__average	False
svm__class_weight
svm__early_stopping	False
svm__epsilon	0.1
svm__eta0	0.0
svm__fit_intercept	True
svm__l1_ratio	0.15
svm__learning_rate	optimal
svm__loss	hinge
svm__max_iter	1000
svm__n_iter_no_change	5
svm__n_jobs
svm__penalty	l2
svm__power_t	0.5
svm__random_state
svm__shuffle	True
svm__tol	0.001
svm__validation_fraction	0.1
svm__verbose	0
svm__warm_start	False

Model Plot

Pipeline(steps=[('scaler', StandardScaler()), ('svm', SGDClassifier())])

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Evaluation Results

Metric	Value
accuracy	0.820274
f1 score	0.695733
precision	0.752005
recall	0.647296

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

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BibTeX:

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eval_method

The model is evaluated using test split, on accuracy, precision, recall and f1.