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Questions tagged [unsupervised-learning]

Unsupervised learning refers to machine learning contexts in which there is no prior 'training' period in which the learning agent is trained on objects of known type. As such, supervised learning includes such disciplines as mathematical clustering, whereby data is segmented into clusters based on the minimisation or maximisation of mathematical properties and not on an attempt to classify by understanding the right context.

Unsupervised learning (or clustering) refers to machine learning algorithms in which there is no 'label' available for the training data and the model tries to learn the underlying manifold. As such, unsupervised learning includes such disciplines as mathematical clustering, whereby data is segmented into clusters based on the minimization or maximization of mathematical properties and not on an attempt to classify by understanding the right context.

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How to plot boudaries around clusters in fuzzy c-means (python)

I am using unsupervised fuzzy c-means for clustering with 3 clusters. From the clustering I obtain a matrix with coordinates of centroids and a matrix with the membership of each point in the three different clusters. I want to plot a decision…
ophelia
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apriori algorithm in python leads to an empty dataset

Trying to run market basket analysis on python. The last step leads to an empty dataset, can someone suggest why and how to fix this ? #importing relevant packages import numpy as np import pandas as pd import matplotlib.pyplot as plt %matplotlib…
Varunn
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Clustering of documents with it's structure

I am working on clustering of documents by looking at it's structure. I have extracted the structure in BERT embeddings variable X in the code below. What I am trying: for num_clusters in np.arange(2,200): model =…
Darth Vader
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Is Kmeans algorithm guaranteed to converge regardless of how the cluster centers are initialized? Why?

K-means is an iterative algorithm that initializes the cluster centers randomly. Is Kmeans algorithm guaranteed to converge regardless of how the cluster centers are initialized? Why?
bharath chandra
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Importance weighted autoencoder doing worse than VAE

I've been implementing VAE and IWAE models on the caltech silhouettes dataset and am having an issue where the VAE outperforms IWAE by a modest margin (test LL ~120 for VAE, ~133 for IWAE!). I don't believe this should be the case, according to both…
magikarp
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Error in build while using keras custom layer

I am trying to train an unsupervised classification model for which i am using deep clustering with my model on Keras. The code I am referring for clustering is this. While running the code i am getting an error in the cutom layer while adding…
hR 312
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How to find the number of clusters when cutting a tree at a certain height in R

I want to find the number of clusters when cutting a tree at given heights. The tree is of class "dendrogram" in R and so I have been using the package dendextend to explore this. Example: # Create a dend: dend <- 1:5 %>% dist %>% hclust %>%…
Luther_Blissett
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How to calculate mean of average distance of points to centroids in Sklearn?

I've been asked to calculate the average distance of each point to its centroid. The data set and number of clusters have been provided and this seems like a very straight forward question (given what k-means clustering does), but I can't seem to…
Brian F.
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Clustering in Mixed Data Types

Why can't we use the Eculidean Distance for Clustering of Categorical Variables and Why we use Gower Distance for the clustering of Categorical Variables. I am just looking for a simple logic and difference of working between the two for clustering…
Karan sehgal
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Anomaly Detection with Autoencoder using unlabelled Dataset (How to construct the input data)

I am new in deep learning field, i would like to ask about unlabeled dataset for Anomaly Detection using Autoencoder. my confusing part start at a few questions below: 1) some post are saying separated anomaly and non-anomaly (assume is labelled)…
CodeNameBobby
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Is it possible to cluster data with grouped rows of data in unsupervised learning?

I am working to setup data for an unsupervised learning algorithm. The goal of the project is to group (cluster) different customers together based on their behavior on the website. Obviously, some sort of clustering algorithm is best for…
Marc Frankel
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Unsupervised population classification

I have a dataset with 2 parameters, looking like this (I have added density contour plots): My goal is to separate this sample in 2 subsets like this: This image comes from QUENCHING OF STAR FORMATION IN SDSS GROUPS:CENTRALS, SATELLITES, AND…
Matt
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Create document clustering based on the text of the document

In Elasticsearch, is possible to group documents that share the most similar texts, without giving an initial query to compare to? I know is possible to query and get MLT("more like this document") but, is possible to cluster documents within an…
A l w a y s S u n n y
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AttributeError: 'NoneType' object has no attribute '_inbound_nodes'

I want to implement the loss function defined here. I use fcn-VGG16 to obtain a map x, and add a activation layer.(x is the output of the fcn vgg16 net). And then just some operations to get extracted features. co_map =…
Teresa Ho
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R : help to analyse cluster content in hierarchical clustering

I have a dataframe of more than 5000 observations. In my attempt to analyse my data using hierarchical clustering, I have 8 clusters, where some of the clusters contain either a few 100 or 1000 individual observations. # Cut tree into 8…
BloopFloopy
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