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Questions tagged [unsupervised-learning]

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

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2 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 ...
28
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2answers
38k views

Choosing the right linkage method for hierarchical clustering

I am performing hierarchical clustering on data I've gathered and processed from the reddit data dump on Google BigQuery. My process is the following: Get the latest 1000 posts in /r/politics ...
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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 ...
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1answer
7k views

K-means Mahalanobis vs Euclidean distance

I currently am trying to cluster "types" of changes on bitemporal multispectral satellite images. I applied a thing called a mad transform to both images, 5000 x 5000 pixels x 5 bands. Each band is a ...
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1answer
407 views

clustering for categorical data with one column for observations

I'm trying to cluster a dataset using 4 variables, all of which are categorical variables. I'd also like to include another numerical variable that's actually the number of observations of another ...
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0answers
9 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
13 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 ...
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3answers
24k views

Unsupervised, supervised and semi-supervised learning

In the context of machine learning, what is the difference between unsupervised learning supervised learning and semi-supervised learning? And what are some of the main algorithmic approaches to ...
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2answers
1k views

Feature selection clustering customer segmentation

based on customer data I want to perform a clustering using different clustering algorithms (K-Means, Expectation Maximization, etc.) in R. The most attributes were engineered pursuing the goal to be ...
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1answer
24 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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1answer
991 views

Unsupervised Outliers detection on time series

So I am looking ways to improve my current implementation of detecting outliers in work schedule. My data set is badge swipes for people. The current implementation finds outliers on in-times and out-...
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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 ...
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2answers
28 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 ...
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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 ...
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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, ...
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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 ...
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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 ...
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 ...
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1answer
478 views

Optimizing cumulative lift in classification

Suppose I have a business problem where I can reach out to 10% of my customers to prevent them from churning. I want to capture as much of the high risk customers I can. Let's say I'm tuning a random ...
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1answer
67 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 ...
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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 ...
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1answer
16 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 ...
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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 ...
1
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2answers
77 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 $c_h$ : ...
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0answers
5 views
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3answers
6k views

Self organizing maps vs k-means, when the SOM has a lot of nodes

On Wikipedia it says: It has been shown that while self-organizing maps with a small number of nodes behave in a way that is similar to k-means, larger self-organizing maps rearrange data in a way ...
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1answer
28 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 ...
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1answer
28 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 ...
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2answers
22 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 ...
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, ...
2
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1answer
192 views

Empty nodes when creating SOM

I am trying to create a SOM map based on records with different discrete classifications (tags) like the example below ...
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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 ...
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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 ...
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1answer
52 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 ...
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1answer
116 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 ...
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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. ...
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1answer
268 views

Assigning weights to variables to calculate rank/score of an Agent

I have data on Agents behavior history. I want to score each of these Agents based on the attributes. Attributes are both Categorical and Continuous.For this, I want to calculate the score by ...
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1answer
201 views

Classification or Clustering Approach for Time Series Data of Flow

I have a dataset which contains time-series data of water flow over time. I have a flow meter connected to a kitchen faucet, and I am trying to cluster or classify specific water usage events. The ...
3
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1answer
23 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
84 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 ...
14
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3answers
8k views

How to choose an optimal number of latent factors in non-negative matrix factorization?

Given a matrix $\mathbf V^{m \times n}$, Non-negative Matrix Factorization (NMF) finds two non-negative matrices $\mathbf W^{m \times k}$ and $\mathbf H^{k \times n}$ (i.e. with all elements $\ge 0$) ...
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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 ...
26
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4answers
26k views

Evaluation measures of goodness or validity of clustering (without having truth labels)

I'm clustering a set of data but I don't have truth document that allow me to evaluate the result of clustering (I have unlabelled data), so I can not use an external evaluation measure. In this case, ...
2
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1answer
212 views

Heuristics for unsupervised or semi-supervised approaches to GIS coordinate data

I have a more conceptual/heuristic question about how to go about formulating a problem in order to take a semi- or unsupervised method of solving it. I'm working on a project with data collected ...
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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
709 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 $K$-...
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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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1answer
330 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 ...
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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 ...