Classifying a Query Point

Classifying a Query Point with KNN

Function Signature

def classify(self, query_point):

Parameters

• query_point: The point for which classification is to be determined.

Return Value

Returns the classification result for the query_point based on the stored values in the KNN instance.

Description

The classify function classifies a given query_point based on the stored values in the KNN instance. The distance between the points is calculated using the Minkowski distance metric with the stored power parameter. The labels of the stored data points are then used to determine the classification of the query_point.

It's important to note that the store_vals function must be called prior to using the classify function to ensure that the necessary values are stored in the KNN instance.

Examples

from deeprai.models import KNN

# Sample data
x_vals = [[1, 2], [2, 3], [3, 4]]
y_vals = [0, 1, 0]
query_point = [2, 2]

# Create an instance of the classifier
classifier = KNN()

# Store the values in the classifier
classifier.store_vals(x_vals, y_vals, p=3, k=2)

# Classify the query_point
result = classifier.classify(query_point)
print(result)  # This will print the classification result for the query_point