Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [unsupervised-learning]

Finding hidden (statistical) structure in unlabelled data, including clustering and feature extraction for dimensionality reduction.

Finding hidden (statistical) structure in unlabelled data, including clustering and feature extraction for dimensionality reduction

Because the items are unlabelled, there's nothing that points toward the "correct" labels, as there is with supervised learning. Unsupervised learning uses methods like clustering and principal components analysis to discover structure.

Reference:
Wikipedia - Unsupervised learning

692 questions
7
votes
1 answer

K-nearest neighbor supervised or unsupervised machine learning?

I've read in several papers that K-nearest neighbor can be supervised or unsupervised learning. Is Knn always unsupervised when one use it for clustering and supervised when one used it for classification? I've to know if there is a unsupervised Knn…
Phil Werner
  • 77
  • 1
  • 1
  • 4
5
votes
3 answers

How do you learn labels with unsupervised learning?

In https://huyenchip.com/machine-learning-systems-design/design-a-machine-learning-system.html#design-a-machine-learning-system-dwGQI5R, I came across the sentence: Similarly, you can use unsupervised learning to learn labels for your data, then…
24n8
  • 1,137
1
vote
0 answers

input data for training USAD network

During reading 'USAD: UnSupervised Anomaly Detection on Multivariate Time Series' paper, to train the autoencoder the authors only used normal datasets. But since this algorithm is used for unsupervised learning, isn't there a chance that a dataset…
roy
  • 11
1
vote
0 answers

Testing if one sample can be from a specific class

Suppose I have 2 customer segments in a bank (private class and another class) defined by the institution itself. and I want to increase the amount of private clients class, bring clients from other class.How could I find similar clients with the…
João Machado
  • 111
1
vote
1 answer

When using "silhouette coefficient" to evaluate an unsupervised model, do we need a labelled dataset?

How does "silhouette coefficient" can find the optimal number of clusters when the dataset is not labelled? Does it need a labelled dataset or is it pure statistics? I mean, when doing unsupervised learning, sometimes, it is used a labelled dataset…
Aizzaac
  • 1,179
1
vote
1 answer

Unsupervised Learning in instances where the researcher determines whether a variable should be small or large?

Sorry if the title is confusing. Essentially, supposed I have two variables; height and weight. My goal is to find the individual who is equally very tall and very skinny (low weight). The idea here is that I, as the researcher, and specifying that…
Nicklovn
  • 891
  • 9
  • 24
1
vote
0 answers

Which algorithm is robust to noisy data? (Decision Tree, K-Mean clustering, HMM)

I assume HMM will be the most robust to noisy data since it derives a generative model compared to Decision Tree and K-Mean? Between decision tree and K-mean, which methods is robust to noisy data? I found K-mean may not work well with outliers.…
pippp
  • 119
0
votes
1 answer

What is a reasonable process to understand a collection of data?

Can someone provide their thoughts on a structured process one might go through to understand a collection of data. The scenario is: you've been given a set of data (features and observations - with descriptions) and been told to "tell me what kind…
BobL
  • 31
  • 1
0
votes
0 answers

Unsupervised Clustering of words from documents in 2 clusters

I'm new to these fields of Machine Learning, and I'll have to use unsupervised clustering of texts, that is make two clusters of words from a document, but without using the widely used K-Means Clustering. I understand there are lots of other…
Helen07
  • 1