Questions tagged [unsupervised-learning]
Finding hidden (statistical) structure in unlabelled data, including clustering and feature extraction for dimensionality reduction.
454 questions
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25 views
Recognizing whether a written and spoken number is the same
For our ML assignment we have three datasets. The challenge is about checking whether a written and spoken number refer to the same number. We're using the MNIST dataset with handwritten numbers, and ...
1
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0answers
27 views
How to measure correlation between two groups of variables?
I have a data set that contain 75 variables of football players . These 75 variables basically measures two different types of information. 30 of those variables related to bio metric information ...
0
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0answers
10 views
Metric learning with respect to an outcome
Suppose I have $n$ datapoints in $p$-dimensional space, and the $p$ variables are highly heterogenous. That is, there is no natural way to combine them. Some are ordinal, some one-hot, some continuous,...
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0answers
18 views
Looking for ways to transform time-series data recorded from object movement into equation describing the movement direction of the object
Looking for some time-series data transformation advice!
I want to know what's the best way to transform data of 9-tuples time series data of IMU (Inertia Measurement Unit) sensor, recorded from a ...
0
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1answer
25 views
Deep learning models for unsupervised semantic segmentation
I am working on semantic segmentation for satellite images using keras and python. It is my understanding that popular models like U-Net require mask images (labels). Are there any unsupervised deep ...
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0answers
8 views
Is there a representer theorem for unsupervised learning (to justify kernel density estimation)?
In supervised learning, we get a representer theorem by considering regularized losses of the following form:
In Kernel Density Estimation, we simply directly assume densities of the form
Could this ...
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0answers
15 views
Predicting user behaviour based on transactional data - flagging “risky” behaviour
Firstly, I'm not sure if this is the right instance of StackOverflow to post on so feel free to ask me to put it elsewhere.
I am exploring the concepts of clustering and "unsupervised" learning for ...
0
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2answers
29 views
R - high dimension data using k means clustering [closed]
The dataset is 1000(observations) x 700(variables), After using pca to do dimension reduction, PC150 explained 85% Variance, so I use this (1000 x 150) data to do k means clustering.
This code was ...
1
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1answer
29 views
Hierarchical clustering for aggregrated features at higher thresholds/levels?
I am trying to use clustering on certain data. The data itself has three natural levels: at the lowest level the elements are fundamental building blocks, at the second level these fundamental ...
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2answers
29 views
Unsupervised Clustering
My research is about comparing K-means and DBSCAN, and Im using unsupervised learning method in clustering.
Is it true that the number of cluster in K-means is also the same number as the unique ...
1
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0answers
12 views
How to interpret LDA (Latent Dirichlet Allocation)?
Say I want to run topic modeling with LDA on The 20 newsgroups text dataset. So basically a dataset with texts where every text belongs to one of 20 categories. I want the LDA to split the documents ...
0
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1answer
21 views
Inference can be the goal of an unsupervised learning method or a semi-supervised learning method or even more of a reinforcement learning method?
I am new to machine learning, and I am reading a pair of machine learning books. These references talk about 2 different learning approaches: Prediction and inference, I understand the difference ...
1
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1answer
17 views
Linking generative, discriminative models to supervised and unsupervised learning
Definitions that I am considering: A generative model learns p(x,y) whereas a discriminative model learns p(y|x=x).
I would like to verify if my understanding is correct by sharing the following ...
2
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1answer
62 views
Scaling data with different importance
I have 9 attributes: x1,x2,x3,x4,...,x9 and I know that the attributes x9 must have the same value in a cluster and the attribute X1 have more importance than others (x2,...,x8)
I'm using Euclidean ...
1
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2answers
36 views
Define attribute importance in unsupervised learning [closed]
I'm using 'NbClust' package to help me to get the "optimal number of clusters" and I noticed in my dataset I have attributes with different importance.
I have 5 attributes: x1,x2,x3,x4,x5 and I know ...
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0answers
6 views
Truncate a Hierarchical Clustering tree in order to get the cophenetic coefficient
I've gone ahead and clustered a dataset using a Euclidian Hierarchical Clustering algorithm:
...
1
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2answers
82 views
In k-means clustering, why sum of squared errors (SSE) always decrease per iteration?
In k-means clustering, why sum of squared errors (SSE) always decrease per iteration?
How can prove it by mathematical derivation of formulas?
k : number of clusters
m : number of examples
$c_h$ : ...
0
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1answer
69 views
Issue in evaluating the performance of my “clustering algorithm” using NMI, ARI when the “ground truth” is available? [duplicate]
(**Edited the question after the initial comments)
Suppose,
Ground_truth_data = [1, 1, 1, 1, 1, 1, 1];
Clustering_result = [1, 1, 1, 1, 1, 1, 2];
Here, as you can see, there are "7" instances of ...
0
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1answer
29 views
How to tune the hyperparameters for oneclass SVM while doing unsupervised learning?
For my task, I am doing unsupervised learning and I am trying to find the best possible value of the parameters gamma and nu in ...
0
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2answers
23 views
How to include percentage variables in PCA + K-means when some values are undefined because the denominator is 0?
I'm trying to do customer segmentation by using PCA to reduce dimensionality and then feeding the resulting principal components into a K-means algo to get at the final segments. Some of my variables ...
4
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0answers
46 views
+50
t-SNE with mixed continuous and binary variables
I am currently investigating the visualisation of high-dimensional data using t-SNE. I have some data with mixed binary and continuous variables and the data appears to cluster the binary data much ...
0
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0answers
15 views
Differentiate Semi-supervised vs Transductive Learning?
Can someone explain the difference between transductive learning and semi-supervised learning? Or is semi-supervised learning a type of transductive learning?
Transductive learning is when we do not ...
0
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1answer
43 views
Finding Optimal Number of Clusters in Expectation Maximization Algorithm
I know that there are several methods (Elbow method, silhouette analysis etc) which can help me to find the best number of clusters.
My questions are:
What are the best methods to use in ...
0
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1answer
30 views
Unsupervised VAE model? [closed]
I would like to use VAE model in unsupervised learning to generate new feature. Most of the examples are supervised and semi-supervised learning.
Where can I find for unsupervised learning or can it ...
0
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1answer
53 views
On feature scaling and weighting for clustering
The issue of feature scaling and weighting for cluster formation has been widely discussed in several books and papers as well as several questions (e.g. here ). To my understanting, variable range is ...
2
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1answer
31 views
Unsupervised clustering of sequence of events to subsequences
I have a big dataset of M sequences of [1 - N] events, where each event has multiple properties (start date, end date, location, ...
0
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1answer
24 views
Unsupervised methods for Detecting Spam
What are some common unsupervised methods used to detect whether something is spam or not? For example, we may be given a large corpus of emails and need to determine whether any one of them is spam. ...
4
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1answer
121 views
How can t-SNE or UMAP embed new (test) data, given that they are nonparametric?
I have started using the UMAP method for dimension reduction which is a similar method to t-SNE, Diffusion Maps, Laplacian Eigenmaps, etc.
The named dimension reduction methods have in common that ...
3
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1answer
24 views
Why are Generative Adversarial Networks classed as unsupervised
The title of the question is basically all I'm asking, but I should explain why GANs don't seem to be unsupervised to me!
Here's my understanding of unsupervised learning:
Unsupervised learning is ...
1
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1answer
89 views
What is the assumption on the distribution of data in gaussian mixture models?
I am reading about Gaussian mixture models from this slide
https://www.ics.uci.edu/~smyth/courses/cs274/notes/EMnotes.pdf
However, I am super confused at the very first line.
It says:
We ...
0
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1answer
27 views
When is it okay to label data yourself? (And semi-supervised learning)
i'm pretty new to machine learning so i think this might be a realy basic question.
Let's imagine the following scenario: I want to classify projects as either active or inactive. Projects can be ...
7
votes
2answers
714 views
Why use a Gaussian mixture model?
I am learning about Gaussian mixture models (GMM) but I am confused as to why anyone should ever use this algorithm.
How is this algorithm better than other standard clustering algorithm such as $K$-...
0
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0answers
44 views
Shared latent spaces
I have two interrelated response variables $A$ and $B$ over each observation $i$ in my data. I am trying to create an unsupervised model where observations could be explained by means of latent spaces(...
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0answers
41 views
Training a neural net as a classifier when there are no labels
I have an ML problem where I have a large data set and in this data set there are N categories. We have no labels. I want to be able to take this data set and use it to train a neural network to ...
0
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1answer
34 views
clustering location based on sorted time
I clustered my dataset based on location using DBSCAN(haversine). Everything is OK until this. However, I'd like to use the time series while I'm clustering my dataset. For example. You were at home ...
1
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0answers
11 views
Find a set of k non-negative vectors that explain most of the variance of the dataset?
I have a set of securities and I am looking for long-only portfolios that explain most of the variance of the set of securities. If it weren't for the long-only requirement, I could have used ...
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1answer
36 views
How to predict without labeled data
I have a data set for patients visiting emergency departments containing following features:
The output variable in this data set is "disposition" - whether a patient becomes admitted or discharged. ...
2
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0answers
42 views
Is there a well established algorithm to match two documents on a semantic level?
I have a set of documents from a wide variety of topics and I would like to retrieve the ones that are more similar to a new document provided. A search based on common words is not good enough, so ...
0
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2answers
35 views
Meaning of Probability Distributions in RBMs
I'm new to machine learning, and am trying to understand some of the basics of Restricted Boltzmann Machines. Unfortunately, I don't have a background in statistics yet beyond a basic understanding, ...
2
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1answer
47 views
Distance metric with characteristics of cosine and Manhattan
I'm working on a project where I want to find similarities between groups of events. So far I have expressed groups of events as vectors of event counts and computing similarities between them. I'm ...
2
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1answer
155 views
Image feature extraction using an Autoencoder combined with PCA
Background: I have fairly large dataset of biomedical images (around 10,000 images) of 1920x1920 pixels (after cropping parts of black borders out). My task is to extract the 200 most important ...
1
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1answer
43 views
Finding similar text - algorithms and evaluation
I've been asked to create a program that will rank similar texts to an input text given a collection of text.
So far I've been using a tdidf representation and cosine similarity with a lot of regex-...
1
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0answers
38 views
How do unsupervised credit scoring models that don't consider historical financial data work?
There seems to be a number of startups (Zest Finance, Credolab etc.) that provide credit scoring schemes that rely exclusively on alternative data without considering users historical financial data ...
2
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1answer
38 views
Clustering circles with different radii with Gaussian Mixture Models
I am interested in clustering $N$ circles in the plane with varying radii using a Gaussian mixture model. The radius of each circle is an integer number $R_i\in\mathbb{N}$ determined from observation. ...
1
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0answers
11 views
How do I calculate ensemble-averaged PCA scores?
For context, please see https://arxiv.org/pdf/1808.00084.pdf (page 6)
I am trying to replicate the results of the above link, which uses dimensionality reduction to observe a phase transition in an ...
0
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1answer
22 views
Searching for the correct approach
I'm writing my Bachelor Thesis within the field of neural networks and I need some preparation of the data I'm using.
Do you have an idea how I am able to identify the four levels in this graph via ...
1
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2answers
149 views
Unsupervised Learning: Train Test division
I have one conceptual question.
In Unsupervised Learning, when I have no labels. The anomaly detection model (Isolation forests, Autoencoders, Distance-based methods etc.), it should fit on a ...
0
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1answer
150 views
When does my unsupervised autoencoder start to overfit?
I am working on anomaly detection using an autoencoder neural network with $1$ hidden layer. This is an unsupervised setting, as I do not have previous examples of anomalies. The input data has ...
2
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0answers
32 views
Understanding short animation about Dirichlet Process Mixture Model
On the wikipedia page of Dirichlet Process,
there is the following video.
I don't get the point of the video.
My first impression was that the video was showing the fitting of one-dimensional data ...
3
votes
2answers
52 views
Confusion in modelling finite mixture model
From the book "Machine Learning a probabilistic Perspective",
I'm reading about finite/infinite mixture models. Particularly at paragraph 25.2.1 it's stated:
The usual representation (of a finite ...
