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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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clustering k-means are not spherical

I'm a beginner in data science and I need your help I'm trying to test unsupervised machine learning with the K-means but I found that the result is not spherical. I normalized, I removed the outliers etc. I tried to find several way to correct it…
Thao Ly
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Compare k-means cluster results with hierarchical clustering

I have a data set(numerical) and I created a k-means algorithm to create clusters based on the features. For K-means, since we assign the number of clusters, I wanted to try a different method and compare the results with k-means. For this I wrote a…
KNB
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How to create a loss-function for an unsupervised-learning model, where the ouput resembles the direct input for a game agent?

I'm trying to setup a deep neuronal network, which predicts the next move for a game agent to navigate a world. To control the game agent it takes two float inputs. The first one controls the speed (0.0 = stop/do not move, 1.0 = max. speed). The…
Tobs
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Get insight from data using machine learning still need manual analysis?

I'm new in machine learning and recently got job to do R&D related to Big Data. The main idea is to get the insight from random collection of big data (I don't know yet what will be the data) and turn it into information and then from information…
Lyn
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Is there any unsupervised clustering technique which can identify numbers clusters itself?

I checked unsupervised clsutering on gensim, fasttext, sklearn but did not find any documentation where I can cluster my text data using unsupervised learn without mentioning numbers of cluster to be identified for example in sklearn KMneans…
user2129623
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Unsupervised learning reduce dimensionality/clustering

I am trying to understand how can I split my data into clusters using unsupervised learning. For example, k-means method. I have 20 columns of data and how can it be projected on 2D surface without losing of necessary information from 18…
renataleb
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Is there any unsupervised learning algorithm that do not not assign k

A traditional unsupervised learning approaches normally needs to assign number of clustering (K) before computing, but what if I do not know the exact number of K and exclude the k out of algorithm, I mean, Is there any unsupervised learning…
bricker
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Classify Database Tables using Unsupervised Machine Learning?

I have a unique use case for ML - I need to classify Database Tables​. They contain meta-data which is Alphanumeric. I know that some tables are similar to others, but I don't know how many groups exist. Is there a way that I can feed this data to a…
swap709
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Are there any limits on k-mean in terms of k points, data dimensionality, and size of data (millions of samples )

I have a dataset consists of 2 million samples. I want to use k-means to cluster this dataset into 2000 clusters. is it ok to use this number of clusters with this data size. note: feature vector size of each sample is 1000
coder
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When I try to run my code, I seem to run with an IndexError

When I try to run my code, I seem to run with an IndexError. def _init_trellis(self, observed, forward=True, init_func=identity): trellis = [ [None for j in range(len(observed))] for i in range(len(self.real_states) + 1)…
Z.N
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Python unsupervised learning for predicting sequence in set of new data

I am using python to model data.Is there anyone to help me to get an idea about to choosing right algorithm for a case. Let's say, If I want to predict the sequence of the operations with mix set of operations. And there are different combinations…
dss
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Unsupervised Classification: Assign classes to to data

I have a set of data from a drill hole, it contains information about different geomechanical properties every 2 meters. I am trying to create geomechanical domains, and assign each point to a different domain. I am trying to use random forest…
CHopp
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k-mode clustering in R returns different cluster sizes with each run

I am using K-Mode clustering to cluster categorical data, but when I cluster the data with the same number of clusters, it return different cluster sizes every time I was expecting that the cluster sizes will be always fixed if I am running it on…
Nobel
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K-Means Clustering Performance Benchmarking

I have data that is 157-dimensional with 688 data-points. With the data I would like to perform clustering. Since K-Means is the simplest algorithm, I have decided to begin with this method. Here is the Sklearn function…
user1274878
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Extract titles and paragraphs from html by elements style

What’s the best datamining strategy to extract titles and paragraphes from an html file basing on the elements style (fontSize, fontWeight, …). I already extracted the text and the fontSize attribute and put them in a csv file, now I need to know…
Mehdi Benmoha
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