Questions tagged [unsupervised-learning]
Finding hidden (statistical) structure in unlabelled data, including clustering and feature extraction for dimensionality reduction.
2
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0answers
31 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
25 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
31 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
26 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
vote
1answer
30 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
23 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
31 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
10 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
21 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
49 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
44 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
27 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
45 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 ...
2
votes
1answer
91 views
Custom Loss Function - Inducing sparsity
From the comments, I realized that my question wasn't clear enough, so I'll start with a short background.
I am trying to construct an attention model that performs classification based on just a ...
2
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0answers
26 views
Performing clustering without a distance matrix
I have n vectors and a matrix of similarity scores between them (e.g. vector 1 score of similarity with vector 4 is 1.3, and with vector 7 is 2.3). This matrix is ...
1
vote
0answers
45 views
Clustering as a method to find and label classes for supervised learning
I'm working on a text classification project. We have around 300k documents (small, 1~2 phrases) and we don't know the set of labels or how many labels there are. The recommended approach to me was ...
1
vote
1answer
23 views
Latent variable in Gaussian Mixture Model
Whenever I look up material pertaining to Gaussian Mixture Models, it always mentions latent variable $z$, where $z \in \{1, ..., K\}$ and is one-hot encoded. I completely understand the objective of ...
0
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2answers
79 views
Why are decision trees considered supervised learning?
It seems to work similar to clustering algorithms, where data does not have to be labeled, and the algorithm creates it's own labels/groups based on feature similarities...
1
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0answers
20 views
clustering objects in point cloud
I am currently working on point cloud data analysis, trying to label objects which are not ground or vegetation e.t.c. So far I tried many clustering algorithms, with moderate success.
In my best ...
0
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0answers
15 views
DBSCAN loops one or several times a data point?
I am trying to construct a model data to facilitate the clustering algortihms execution in terms of searching for data point in the dataset. This model is a set of connections between points such that ...
3
votes
2answers
62 views
External validation of clustering requires labels, but why cluster at all if you have labels?
There are two types of validation in clustering, using:
Internal indexes: Used to measure the goodness of a clustering structure without respect to external information (e.g., sum of squared errors)...
1
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1answer
23 views
How can I tell if an Autoencoder is encoding my data properly?
Autoencoders can be classified as a method of unsupervised learning, and unsupervised learning often comes with a problem where it's hard to tell if the model is working properly.
However, some ...
1
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0answers
60 views
Clustering Noisy Data [closed]
There are various ways to cluster data. Some require the data first to be scaled to have a mean of $0$ and standard deviation of $1$. However, others do not mention if the data should be scaled at all....
0
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1answer
39 views
Is clustering subsequences of time-series still meaningless with unsupervised learning?
In the paper "Clustering of Time Series Subsequences Is Meaningless" Keoh et al. claim that breaking a time-series into chunks (sometimes called lags) of fixed-size using the rolling window method ...
1
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1answer
37 views
Clustering data that includes a categorical variable with many different levels
I'm looking to cluster data on apartments. I have the following variables for each apartment:
Latitude
Longitude
Price
Number of bathrooms
Number of bedrooms
Amenities (washer, gym, etc.)
The ...
1
vote
0answers
11 views
Performance of Hierarchical Temporal Memory on unsupervised online anomaly detection problems
I'm looking for an algorithm to detect anomalies in streaming data (server metrics). The detection needs to be near-real time and unsupervised (labeled data will never be available, unfortunately, and ...
2
votes
0answers
14 views
What are the simple methods to do an unsupervised cluster to stock return time series?
I am a student in finance and I am working on my thesis project. I am interested in doing a clustering to stock time series. I first read the paper 'Time-series clustering – A decade review' from ...
2
votes
3answers
82 views
How to find strongly connected subgraphs in a graph? [duplicate]
I have a simple, undirected graph where I'd like to detect "natural" subgraphs where vertices are connected intensively internally but sparsely externally. The problem is that I have no exact hint ...
0
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0answers
16 views
What are some good probabilistic modeling approaches for co-occurance of words in large corpus of short documents?
I'd be very grateful for some advice in finding a modeling approach and toolset for a NLP problem I have.
I need to learn a joint distribution of tokens in a corpus of docs. I have on the order of ...
0
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0answers
118 views
Action space for Reinforcement Learning implementation
I am confused about how to set action space for my application for which I like to use Reinforcement Learning to select the best instance.
I have two groups of instances.
Group_a and Group_b, ...
2
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0answers
63 views
what's the difference between semi-supervised learning and partially supervised learning? [closed]
Isn't every semi-supervised problem also a partially supervised learning problem and vice versa?
-1
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1answer
12 views
Which clustering technique to use for 1D data with 2 Gaussian distributions without training data?
I have 1D data which is likely to be 2 Gaussian distributions overlapped. I do not have training data but I know one should be slightly high contributed from few points and another is very broad with ...
-1
votes
1answer
23 views
K-means in R: complete case analysis followed by nearest-neighbor assignment for partial data
I have a dataset of 3K observations with only 162 being a complete case.
I have read here that it is possible to run knn on the complete cases and then conduct a nearest neighbour assignment for ...
1
vote
1answer
67 views
Is a chi-square test for independence appropriate on a contingency table where one category is the unsupervised learning cluster?
I have a data set that has been partitioned into four clusters by executing a clustering algorithm that used principal components from a principal component analysis (PCA). I then make a contingency ...
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0answers
19 views
When applying PCA to a dataset consisting of regression coefficients, should one use PCA on correlation or on covariance?
This is a follow-up question from the post: PCA on correlation or covariance?
The accepted answer quotes:
You tend to use the covariance matrix when the variable scales are
similar and the ...
0
votes
1answer
72 views
How to get meaningful results from Softmax activation in Deep Unsupervised Clustering Network
I found this interesting paper regarding deep unsupervised clustering and am looking to mimic some of the things done, however there is one thing that is not clear to me. In the paper, they use a ...
1
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0answers
43 views
What exactly is semisupervised learning?
I have come across two descriptions of what semisupervised learning is, where one would have a small set $\mathcal{L}$ of labeled data and a larger set $\mathcal{U}$ of unlabeled data. The first ...
0
votes
1answer
35 views
Cross Validation in application of clustering on a collection of similarly behaving time series
I'm trying to understand how and at which point can one apply Cross Validation for time series data. If i'm not wrong CV increases generalisation so that our model has less bias in case the data is ...
1
vote
2answers
40 views
Unsupervised learning with missing features
Assume I have a set of N vectors with M features each. If I want to create a latent space to project these vectors into, there are a variety of techniques available to me, such as Principle Component ...
1
vote
1answer
948 views
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 ...
-1
votes
1answer
59 views
clustering VS supervised classification, in the case of very small database
I'm trying to classify/cluster subjects according to 4 features in two classes: healthy and sick.
Two things to know: I know the labels/classes of each subject + I only have 40 subjects (in total: ...
1
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0answers
34 views
Unsupervised Text Clustering Project: How to get started? [closed]
I work for a manufacturing company where robust databases and data integrity have not always been a priority. I have a very messy and finite list of 13,102 tool descriptions. I need to find out how ...
0
votes
1answer
151 views
unsupervised classification VS supervised classification when data labels are known
Can someone give me some scenario where it's better to use clustering (unsupervised classification) than supervised classification such as SVM ? I mean in a case where you know the data labels/classes....
14
votes
3answers
445 views
What *is* an Artificial Neural Network?
As we delve into Neural Networks literature, we get to identify other methods with neuromorphic topologies ("Neural-Network"-like architectures). And I'm not talking about the Universal Approximation ...
1
vote
1answer
52 views
Is it possible to select features from completely unlabeled data?
I have seen many examples of using semi-supervised learning to reduce the the number of features in a data set, but I am wondering if it is possible to somehow reduce features with purely unlabeled ...
1
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0answers
19 views
how many data points for effective LDA (clustering)?
Is there an advisable number of data points recommended to be able to effectively use LDA (Linear discriminant analysis)? I know this is a very open-ended question: but how many is enough?
2
votes
1answer
73 views
“Reverse” clustering?
There is a lot of content about how to cluster, say, customers (k-means, EM clustering, etc.).
However, is there a way to reverse cluster customers? Meaning, let's say I have 20 customers, and want ...
0
votes
1answer
204 views
Training and testing an autoencoder on very sparsely populated data
I am exploring the possibility of using a deep autoencoder neural net to build a recommender system. I am firstly testing the model's performance on the traditionally used benchmark of the Movielens ...
0
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0answers
55 views
Affinity Propagation - number of clusters?
I am working on a clustering exercise where I am unsure about how to decide what is the appropriate number of clusters for my dataset. This is an unsupervised learning exercise so I have no way to ...
0
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0answers
74 views
Factor Scores and Clustering
I used self organizing map to cluster factor scores. I used 5 variables for clustering and at the end, I have 4 clusters. Some factor score means are negative. How am I supposed to interpret these ...
