Weighted KMeans Clustering for Geolocational Problem
Project description
Weighted KMeans Clustering for Geolocational Problem
Repo for weighted k means clustering for specifically geo locational problems.
For an example and mathematical explanation:
https://emrahcimren.github.io/data%20science/Greenfield-Analysis-with-Weighted-Clustering/
Prerequisites
Install environment.yml for prerequisites.
conda env create -f environment.yml
To recreate environment.yml
conda env export > environment.yml
To create requirements.txt from environment.yml
pip freeze > requirements.txt
Installation
pip install cimren-wkmeans-geo
Inputs
input_locations is a pandas dataframe with the following format.
LOCATION_NAME | LATITUDE | LONGITUDE | WEIGHT | VOLUME |
---|---|---|---|---|
LOC 0 | -27.0065 | 170.583 | 1 | 10 |
number_of_clusters: Number of clusters to be created
minimum_elements_in_a_cluster: Minimum elements in a cluster
maximum_elements_in_a_cluster: Maximum elements in a cluster
maximum_volume_in_a_cluster: Maximum volume that can fit in a cluster; if set to None, then it is disabled
maximum_iteration: How many maximum number of steps the algorithm takes to stop if it does not find the solution
enable_minimum_maximum_elements_in_a_cluster: True/False to enable minimum and maximum cluster size
objective_range: Acceptable difference between objectives at each iteration
Data
Package has a sample data set
from wkmeans_geo.src import data
data.locations_test
data.number_of_clusters
data.minimum_elements_in_a_cluster
data.maximum_elements_in_a_cluster
data.maximum_volume_in_a_cluster
data.maximum_iteration
data.enable_minimum_maximum_elements_in_a_cluster
data.objective_range
How to use
from wkmeans_geo.src import data
from wkmeans_geo import wkmeans_clustering as wkc
clusters, locations_with_clusters = wkc.calculate_clusters(
data.locations_test,
data.number_of_clusters,
data.minimum_elements_in_a_cluster,
data.maximum_elements_in_a_cluster,
data.maximum_volume_in_a_cluster,
data.maximum_iteration,
data.objective_range,
data.enable_minimum_maximum_elements_in_a_cluster)
Project details
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