NearestCentroid (Beta)¶
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NearestCentroid(name: str,
cursor = None,
p: int = 2)
Creates a NearestCentroid object by using the k-nearest centroid algorithm. This object uses pure SQL to compute all the distances and final score.
⚠ Warning: This function uses the p-distance, which makes it very sensitive to unnormalized data.
Parameters¶
| Name | Type | Optional | Description |
|---|---|---|---|
name | str | ❌ | Name of the model to be stored in the database. |
cursor | DBcursor | ✓ | Vertica DB cursor. |
p | int | ✓ | The p corresponding to the one of the p-distance (distance metric used during the model computation). |
Attributes¶
After the object creation, all the parameters become attributes. The model will also create extra attributes when fitting the model:
| Name | Type | Description |
|---|---|---|
centroids_ | tablesample | The final centroids. |
classes_ | list | List of all the response classes. |
input_relation | str | Training relation. |
X | list | List of the predictors. |
y | str | Response column. |
test_relation | str | Relation to use to test the model. All the model methods are abstractions which will simplify the process. The test relation will be used by many methods to evaluate the model. If empty, the training relation will be used as test. You can change it anytime by changing the test_relation attribute of the object. |
Methods¶
| Name | Description |
|---|---|
| classification_report | Computes a classification report using multiple metrics to evaluate the model (AUC, accuracy, PRC AUC, F1...). In case of multiclass classification, it will consider each category as positive and switch to the next one during the computation. |
| confusion_matrix | Computes the model confusion matrix. |
| cutoff_curve | Draws the model Cutoff curve. |
| deploySQL | Returns the SQL code needed to deploy the model. |
| fit | Trains the model. |
| get_attr | Returns the model attribute. |
| get_params | Returns the model Parameters. |
| lift_chart | Draws the model Lift Chart. |
| prc_curve | Draws the model PRC curve. |
| predict | Predicts using the input relation. |
| roc_curve | Draws the model ROC curve. |
| score | Computes the model score. |
| set_cursor | Sets a new DB cursor. |
| set_params | Sets the parameters of the model. |
| shapExplainer | Creates a shapExplainer for the model. |
| to_sklearn | Converts the Vertica Model to an sklearn model. |
Example¶
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from verticapy.learn.neighbors import NearestCentroid
model = NearestCentroid(p = 2)
display(model)