metadata

library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: NYC_SQF_ARR_KNN.pkl
widget:
  - structuredData:
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      KNIFE_CUTTER_FLAG:
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      OTHER_CONTRABAND_FLAG:
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      OTHER_WEAPON_FLAG:
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      SEARCHED_FLAG:
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      STOP_LOCATION_PRECINCT:
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      SUSPECT_BODY_BUILD_TYPE:
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      SUSPECT_RACE_DESCRIPTION:
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      SUSPECT_REPORTED_AGE:
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      SUSPECT_SEX:
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Model description

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Intended uses & limitations

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Training Procedure

[More Information Needed]

Hyperparameters

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Hyperparameter	Value
memory
steps	[('scaler', MinMaxScaler()), ('knn', KNeighborsClassifier(n_neighbors=15))]
verbose	False
scaler	MinMaxScaler()
knn	KNeighborsClassifier(n_neighbors=15)
scaler__clip	False
scaler__copy	True
scaler__feature_range	(0, 1)
knn__algorithm	auto
knn__leaf_size	30
knn__metric	minkowski
knn__metric_params
knn__n_jobs
knn__n_neighbors	15
knn__p	2
knn__weights	uniform

Model Plot

Pipeline(steps=[('scaler', MinMaxScaler()),('knn', KNeighborsClassifier(n_neighbors=15))])

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Evaluation Results

Metric	Value
accuracy	0.854806
f1 score	0.740402
precision	0.795157
recall	0.692702

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

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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.