Page 22 - Data Science Algorithms in a Week

Classification Using K Nearest Neighbors

By applying this procedure to every data point, we can complete the graph as follows:

Note that sometimes a data point can be distanced from two known classes with the same
distance: for example, 20 degrees Celsius and 6km/h. In such situations, we could prefer one
class over the other or ignore these boundary cases. The actual result depends on the
specific implementation of an algorithm.

Implementation of k-nearest neighbors

algorithm

We implement the k-NN algorithm in Python to find Mary's temperature preference. In the
end of this section we also implement the visualization of the data produced in example
Mary and her temperature preferences by the k-NN algorithm. The full compilable code
with the input files can be found in the source code provided with this book. The most
important parts are extracted here:

# source_code/1/mary_and_temperature_preferences/knn_to_data.py
# Applies the knn algorithm to the input data.

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