Update README.md

README.md

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 # Model description
 
-[More Information Needed]
+This is a logistic regression model trained on customers' credit card risk data in a bank using sklearn library.
+The model predicts whether a customer is worth issuing a credit card or not. The full dataset can be viewed at the following link: https://huggingface.co/datasets/saifhmb/CreditCardRisk
 
-## Intended uses & limitations
 
-[More Information Needed]
 
 ## Training Procedure
 
-[More Information Needed]
-
+The data preprocessing steps applied include the following:
+- Dropping high cardinality features, specifically ID
+- Transforming and Encoding categorical features namely: GENDER, MARITAL, HOWPAID, MORTGAGE and the target variable, RISK
+- Splitting the dataset into training/test set using 85/15 split ratio
+- Applying feature scaling on all features
+  
 ### Hyperparameters
 
 <details>
@@ -125,6 +128,9 @@ widget:
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See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-13 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-13" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;preprocessor&#x27;,ColumnTransformer(remainder=&#x27;passthrough&#x27;,transformers=[(&#x27;cat&#x27;,Pipeline(steps=[(&#x27;onehot&#x27;,OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),[&#x27;GENDER&#x27;, &#x27;MARITAL&#x27;,&#x27;HOWPAID&#x27;, &#x27;MORTGAGE&#x27;]),(&#x27;num&#x27;,Pipeline(steps=[(&#x27;scale&#x27;,StandardScaler())]),Index([&#x27;AGE&#x27;, &#x27;INCOME&#x27;, &#x27;NUMKIDS&#x27;, &#x27;NUMCARDS&#x27;, &#x27;STORECAR&#x27;, &#x27;LOANS&#x27;], dtype=&#x27;object&#x27;))])),(&#x27;classifier&#x27;, LogisticRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-97" type="checkbox" ><label for="sk-estimator-id-97" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[(&#x27;preprocessor&#x27;,ColumnTransformer(remainder=&#x27;passthrough&#x27;,transformers=[(&#x27;cat&#x27;,Pipeline(steps=[(&#x27;onehot&#x27;,OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),[&#x27;GENDER&#x27;, &#x27;MARITAL&#x27;,&#x27;HOWPAID&#x27;, &#x27;MORTGAGE&#x27;]),(&#x27;num&#x27;,Pipeline(steps=[(&#x27;scale&#x27;,StandardScaler())]),Index([&#x27;AGE&#x27;, &#x27;INCOME&#x27;, &#x27;NUMKIDS&#x27;, &#x27;NUMCARDS&#x27;, &#x27;STORECAR&#x27;, &#x27;LOANS&#x27;], dtype=&#x27;object&#x27;))])),(&#x27;classifier&#x27;, LogisticRegression())])</pre></div></div></div><div class="sk-serial"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-98" type="checkbox" ><label for="sk-estimator-id-98" class="sk-toggleable__label sk-toggleable__label-arrow">preprocessor: ColumnTransformer</label><div class="sk-toggleable__content"><pre>ColumnTransformer(remainder=&#x27;passthrough&#x27;,transformers=[(&#x27;cat&#x27;,Pipeline(steps=[(&#x27;onehot&#x27;,OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),[&#x27;GENDER&#x27;, &#x27;MARITAL&#x27;, &#x27;HOWPAID&#x27;, &#x27;MORTGAGE&#x27;]),(&#x27;num&#x27;,Pipeline(steps=[(&#x27;scale&#x27;, StandardScaler())]),Index([&#x27;AGE&#x27;, &#x27;INCOME&#x27;, &#x27;NUMKIDS&#x27;, &#x27;NUMCARDS&#x27;, &#x27;STORECAR&#x27;, &#x27;LOANS&#x27;], dtype=&#x27;object&#x27;))])</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-99" type="checkbox" ><label for="sk-estimator-id-99" class="sk-toggleable__label sk-toggleable__label-arrow">cat</label><div class="sk-toggleable__content"><pre>[&#x27;GENDER&#x27;, &#x27;MARITAL&#x27;, &#x27;HOWPAID&#x27;, &#x27;MORTGAGE&#x27;]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-100" type="checkbox" ><label for="sk-estimator-id-100" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div></div></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-101" type="checkbox" ><label for="sk-estimator-id-101" class="sk-toggleable__label sk-toggleable__label-arrow">num</label><div class="sk-toggleable__content"><pre>Index([&#x27;AGE&#x27;, &#x27;INCOME&#x27;, &#x27;NUMKIDS&#x27;, &#x27;NUMCARDS&#x27;, &#x27;STORECAR&#x27;, &#x27;LOANS&#x27;], dtype=&#x27;object&#x27;)</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-102" type="checkbox" ><label for="sk-estimator-id-102" class="sk-toggleable__label sk-toggleable__label-arrow">StandardScaler</label><div class="sk-toggleable__content"><pre>StandardScaler()</pre></div></div></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-103" type="checkbox" ><label for="sk-estimator-id-103" class="sk-toggleable__label sk-toggleable__label-arrow">remainder</label><div class="sk-toggleable__content"><pre>[]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-104" type="checkbox" ><label for="sk-estimator-id-104" class="sk-toggleable__label sk-toggleable__label-arrow">passthrough</label><div class="sk-toggleable__content"><pre>passthrough</pre></div></div></div></div></div></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-105" type="checkbox" ><label for="sk-estimator-id-105" class="sk-toggleable__label sk-toggleable__label-arrow">LogisticRegression</label><div class="sk-toggleable__content"><pre>LogisticRegression()</pre></div></div></div></div></div></div></div>
 
 ## Evaluation Results
+- The target variable, RISK is multiclass. In sklearn, precision and recall functions have a parameter called,
+average. This parameter is required for a multiclass/multilabel target. average = 'micro' was used to calculate
+the precision and recall metrics globally by counting the total true positives, false negatives and false positives
 
 | Metric    |    Value |
 |-----------|----------|
@@ -136,26 +142,13 @@ widget:
 
 ![Confusion Matrix](confusion_matrix.png)
 
-# How to Get Started with the Model
 
-[More Information Needed]
 
 # Model Card Authors
 
-This model card is written by following authors:
-
-[More Information Needed]
+This model card is written by following authors: Seifullah Bello
 
 # 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.
+You can contact the model card authors through following channels: [email protected]
 
-**BibTeX:**
-```
-[More Information Needed]
-```