unsupervised-learning.md

description
A machine learning approach that uses unlabeled data

Unsupervised Learning

PostgresML supports several clustering algorithms for unsupervised learning. Models can be trained using pgml.train on unlabeled data to identify groups within the data.

Training

To build clusters on a given dataset, we can use the table or a view. Since clustering is an unsupervised algorithm, we don't need a column that represents a label as one of the inputs to pgml.train.

API

In pgml.train you need to set cluster as task and pass a project_name. Most parameters are optional.

pgml.train(
    project_name TEXT,
    task TEXT DEFAULT NULL,
    relation_name TEXT DEFAULT NULL,
    algorithm TEXT DEFAULT 'linear',
    hyperparams JSONB DEFAULT '{}'::JSONB
)

Algorithms

Algorithm	Reference
affinity_propagation	AffinityPropagation
birch	Birch
kmeans	K-Means
mini_batch_kmeans	MiniBatchKMeans

Example

This example trains models on the sklean digits dataset -- which is a copy of the test set of the UCI ML hand-written digits datasets. This demonstrates using a table with a single array feature column for clustering. You could do something similar with a vector column.

SELECT pgml.load_dataset('digits');

-- create an unlabeled table of the images for unsupervised learning
CREATE VIEW pgml.digit_vectors AS
SELECT image FROM pgml.digits;

-- view the dataset
SELECT left(image::text, 40) || ',...}' FROM pgml.digit_vectors LIMIT 10;

-- train a simple model to classify the data
SELECT * FROM pgml.train('Handwritten Digit Clusters', 'cluster', 'pgml.digit_vectors', hyperparams => '{"n_clusters": 10}');

-- check out the predictions
SELECT target, pgml.predict('Handwritten Digit Clusters', image) AS prediction
FROM pgml.digits
LIMIT 10;

Other Algorithms

SELECT * FROM pgml.train('Handwritten Digit Clusters', algorithm => 'affinity_propagation');
SELECT * FROM pgml.train('Handwritten Digit Clusters', algorithm => 'birch', hyperparams => '{"n_clusters": 10}');
SELECT * FROM pgml.train('Handwritten Digit Clusters', algorithm => 'kmeans', hyperparams => '{"n_clusters": 10}');
SELECT * FROM pgml.train('Handwritten Digit Clusters', algorithm => 'mini_batch_kmeans', hyperparams => '{"n_clusters": 10}');