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README.md

@@ -27,7 +27,6 @@ The model achieves approximately 87% accuracy. Its performance is strongest on m
 ```python
 from skops.io import load
 model = load('model.skops')
-# X must contain the same feature columns used during training
 predictions = model.predict(X)
 ```
 
@@ -137,3 +136,11 @@ div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
 }#sk-container-id-2 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
 }
 </style><div id="sk-container-id-2" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>DecisionTreeClassifier(max_depth=6)</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"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;DecisionTreeClassifier<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html">?<span>Documentation for DecisionTreeClassifier</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>DecisionTreeClassifier(max_depth=6)</pre></div> </div></div></div></div>
+
+## Figures
+
+### Confusion Matrix
+![Confusion Matrix](confusion_matrix.png)
+
+### Decision Tree
+![Decision Tree](decision_tree6.png)