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saifhmb
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Credit-Card-Risk-Model

Tabular Classification
Scikit-learn
skops
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Credit-Card-Risk-Model / README.md
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metadata
library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: skops-1j3gdp7x.pkl
widget:
  - structuredData:
      x0:
        - 1.0086665077175379
        - 1.0086665077175379
        - -0.9914079553041198
      x1:
        - -1.0086665077175376
        - -1.0086665077175376
        - 0.99140795530412
      x10:
        - -0.22650043789522045
        - 1.0087085512107812
        - -1.1535683034040811
      x11:
        - -0.3931869525722032
        - -1.2502276872280191
        - -0.3931869525722032
      x12:
        - -0.22475360373860484
        - -1.2736037545187613
        - -1.2736037545187613
      x13:
        - -0.36644465957257716
        - -0.36644465957257716
        - -0.36644465957257716
      x14:
        - -0.43989052441881077
        - -1.6043722933752058
        - -0.43989052441881077
      x2:
        - -0.5244627009562925
        - -0.5244627009562925
        - -0.5244627009562925
      x3:
        - -1.0038424733297755
        - -1.0038424733297755
        - 0.9961722347560998
      x4:
        - 1.594238352724291
        - 1.594238352724291
        - -0.6272587773911873
      x5:
        - -0.9810049179827242
        - 1.0193628815402107
        - 1.0193628815402107
      x6:
        - 0.981004917982724
        - -1.019362881540211
        - -1.019362881540211
      x7:
        - 1.901326970246757
        - -0.525948464229825
        - -0.525948464229825
      x8:
        - -1.9013269702467568
        - 0.5259484642298251
        - 0.5259484642298251
      x9:
        - -0.7015627248979232
        - 0.8218167103592607
        - -1.3109144990007968

Model description

[More Information Needed]

Intended uses & limitations

[More Information Needed]

Training Procedure

[More Information Needed]

Hyperparameters

Click to expand
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 0.699187
precision 0.699187
recall 0.699187

Confusion Matrix

Confusion Matrix

How to Get Started with the Model

[More Information Needed]

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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