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Machine Learning Resources

What is the difference between Supervised and Unsupervised Learning

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Supervised learning and Unsupervised learning are the two main categories of machine learning algorithms. The primary differences between supervised and unsupervised learning are:

  • the presence of labeled data for supervised methods vs the absence of labeled data for unsupervised methods
  • the ease of objective evaluation and comparison of models in supervised learning as opposed to (somewhat) subjective evaluations in unsupervised learning

Explaining further, in supervised learning the algorithms are trained on labeled datasets with a goal to learn a mapping function that can predict the output on a new, unseen data. Whereas in unsupervised learning the algorithms are trained on unlabeled datasets with a goal to find patterns and relationships in the data.

Since the supervised methods use labeled datasets it is easy to do objective model evaluations and comparisons by splitting the data into training and test sets. However, for unsupervised methods the lack of a definitive output variable makes it difficult to do a truly objective model evaluation.

The following table summarizes the differences between Supervised and Unsupervised learning:

Supervised LearningUnsupervised Learning
Input DataLabeled training data
(output variable)
Unlabeled training data
(no output variable)
Objective Learn a function to predict the output variableFind hidden patterns, relationships, and associations in the data
Problem TypesPredict:
– a continuous variable (Regression)
– a categorical variable (Classification)
– Group similar data points together (Clustering)
– Find outliers in the data (Anomaly Detection)
– Reduce the number of features (Dimensionality Reduction)
Model EvaluationsObjective evaluation and model comparison methodsLack of a definitive output variable makes it difficult to do truly definitive evaluations and model comparisons
Example Applications– Predict the selling price for a house
– Classify an image into a dog image or a cat image
– Group similar news articles together
– Identify fraudulent financial transactions
– Visualize high dimensional datasets

This image sourced from succinctly describes the difference between supervised and unsupervised learning:

Supervised vs Unsupervised Learning (Source: Supervised vs Unsupervised Learning: Key Differences)

Illustrative examples

Source: AIML Research

Video Explanation

The following video from provides a good overview of Supervised and Unsupervised learning methods; and compares the two by using various examples.

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