Questions tagged [unsupervised-learning]

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

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2answers
86 views

customer segmentation with unbalanced data

I am trying to do a customer segmentation on my transactional data and I am struggling a little bit on the best approach. Since it is an unsupervised model I can throw it to any algorithm and get some ...
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1answer
30 views

How would you quantify an experience into a score without labeled data

How would you approach a scenario where you have to quantify an abstract notion like “customer experience” without having any labeled data? So basically what you have are bunch of variables that you ...
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1answer
132 views

Clustering with custom criterion (minimum cluster weight)

Edit: following comment from @anony-mousse, I'm changing the question to search for a general clustering approach that matches this criterion (minimum weight per cluster). I am to use a clustering ...
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3answers
733 views

What kind of learning is needed for anomaly detection? Supervised learning, semi-supervised learning or unsupervised learning?

I am doing anomaly detection recently, one of the methods is using AEs model to learn the pattern of normal samples. Determine it as an abnormal sample if it doesn’t match the pattern of normal ...
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0answers
321 views

sklearn & Meanshift for NLP only returns 1 cluster

I am using sklearn.clustering to work with some text data and the MeanShift algorithm. I have: Done all standard NLP data prep like lemmatizing, removing stop ...
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1answer
50 views

How to cluster text-based software requirements

I'm beginner in deep learning and I'd like to cluster text-based software requirements by themes (words similarities/frequency of words) using neural networks. Is there any example/tutorial/github ...
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0answers
27 views

I need help interpreting this PCA plot

I have a dataset of 116 observations and 10 numeric variables. The dataset contains information about healthy patients and patients attained with breast cancer. I did a PCA plot showing the cluster of ...
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1answer
46 views

what is a good performance measure for comparing different neural network architectures in unsupervised clustering task?

What is a good measure to use when trying to decide between picking unsupervised clustering NN architectures? There seems to some ideas here, but i am trying to find out feedback/suggestions from ...
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1answer
173 views

Kmeans cluster validation when I have labeled test data

I'm trying to implement the unsupervised k-means algorithm for sentiment analysis of imdb movie dataset created by stanford. The steps that I followed is : 1) Load the comments 2) Apply tokenization ...
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2answers
283 views

Unsupervised text clustering using a driving list

I want to apply unsupervised clustering on a set of short texts, which I need to divide into 2 clusters. Also I know that one of my clusters is likely to contain some words (non-exhaustive list) and ...
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0answers
518 views

HMM - Matlab for data set to detect anomaly

I have a dataset of oil temperatures. The time series consist of 100 hours of measurement at every second. There is an anomaly in the data that I would like to detect using Hidden Markov Models (HMM). ...
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2answers
92 views

Theoretical treatment of unlabeled samples

In a typical supervised learning setting with a few positive and a few negative examples, it is clear that unlabeled data carries some information that can benefit learning and that is not captured in ...
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1answer
44 views

Unsupervised Sentimental Analysis in R

How would you evaluate unsupervised sentimental analysis? I am reading on evaluating sentimental analysis and learning that much of the classification models that are being used, the data has target/...
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2answers
31 views

How can I perform clustering on a list of words and ratings as columns?

I want to perform clustering to give words meaning like good, neutral and bad. My dataset is in the format : ...
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1answer
38 views

What is the most straightforward way to discover clusters in data? [closed]

I'm planning on extracting a number of word vector distances from a data set, and I want to be able to detect clusters within that set, with an undefined number of clusters that are dynamically ...
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0answers
17 views

Design of loss function for unsupervised learning neural network

Input is a string: get filename (e.x., get file.txt get hello.txt) output: predict a number between 1 to 15 Property need to be translated into loss function: define in the loss function that, even if ...
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1answer
20 views

Detect time pattern in sequence of events

I have a time series with a timestamp and an associated event: Time Event 1 A 2 B 3 C T A I was wondering if there is a technique/method to figure out which events most often precede others in a ...
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1answer
39 views

Self Organizing Map (SOM)

How do you use SOM as a supervised learning technique? Which approach can be added to SOM to turn it to supervised learning?
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1answer
31 views

Does Anomaly Detection Algorithm works when the features are not correlated?

I am working on an Anomaly Detection Problem and the algorithm I used is an Autoencoder Multivariate Gaussian. The problem with my data is that it is unlabeled and not correlated. For example, let's ...
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1answer
31 views

How to explain the results from this kmeans?

I got the following results by using k-means algorithm. There are $10$ elements in Cluster $0$ and $3$ elements in Cluster $1$. Do you think it makes sense and it might be an acceptable result? How ...
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1answer
20 views

Multi-Data Type Clustering

I have data with text, categorical, and numeric columns and would like to find a clustering algorithm that can handle all three of these data types. I am struggling to find a solution that would ...
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1answer
188 views

How to use K-Means to detect users anomaly in Access Control

I'm currently working on access control project, Smart Lock to be more spesific. Like the other smart lock system, the system required user's authentication to open the door. I'm using RFID as ...
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1answer
78 views

Text standardisation for manually entered data

I am working on a project that involves dealing with manually entered text data. I have a dataset of customs records where the customs officers manually enter the name and address of companies ...
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1answer
6k views

Cluster tendency using Hopkins statistic implementation in Python

The Hopkins statistic, is a statistic which gives a value which indicates the cluster tendency, in other words: how well the data can be clustered. If the value is between {0.01, ...,0.3}, the data ...
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2answers
370 views

Clustering data set with multiple dimensions

I have a data set which is similar to the following: It is recipe data along with the composition of the recipe (in %) I have 91 recipes and 40 ingredients in total. I want to be able to cluster ...
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1answer
112 views

Clustering for variables with large amount of categories

I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do ...

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