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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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Does StandardScaler() maintain order?

I'm using StandardScaler to transform data before providing training dataset to clustering model. X = StandardScaler().fit_transform(X_train) Assume, clf is the unsupervised cluster model, I'm predicting the labels as follows: y =…
Gordon Knot
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Multiple features clustering

I want to know how I could perfom a cluster analysis with multiple features. Let's consider, for example, that I have a set of features for each object (I have a lot of objects). And each of these features has a particular dimension (Feature A is a…
Nana89
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Cutting dendrogram at highest level of purity

I am trying to create program that cluster documents using hierarchical agglomerative clustering, and the output of the program depends on cutting the dendrogram at such a level that I get maximum purity. So following is the algorithm I am working…
mdanishs
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Kohonen network - how to choose the map parameters

http://xmipp.cnb.csic.es/NewXmipp/Web_Site/public_html/NewXmipp/Applications/Src/SOM/Help/som.html Example 1: Maps a set of data stored in "test.dat" file into a 10x7 hexagonal map. in this case , they already use 10*7 . this parameters depend on…
user2645553
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How to extend upper and lower limits of ANFIS membership function in MATLAB?

I am trying to implement ANFIS on MATLAB. My input data operating range is 0-180, but MATLAB generates ANFIS membership function limits within 0-10. How to extend it from 0 to 180? Also another problem is my ANFIS input data is something like "data…
Binja
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Lightweight unsupervised learning method like Self organizing maps

I am trying to develop a lightweight system that uses an unsupervised learning method that uses system parameters such as CPU, RAM utilization to train an anomaly detection system. I could not think of anything beyond a Self organizing map. Is there…
user1908488
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Does matlab's k-mean recompute the cluster membership of seeds?

I am unable to find the details of matlab's k-mean about seeds. That if matlab's k-mean recomputes the cluster assignment of Xs seeds, which is subset of data set X matrix. Or these seeds are only used for initial centered location and are not…
Sid Ali
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scikit-learn documentation example: 'got an unexpected keyword argument'

When running this example from the scikit-learn documentation, I get the error v_measure_score() got an unexpected keyword argument 'beta': from sklearn import metrics labels_true = [0, 0, 0, 1, 1, 1] labels_pred = [0, 0, 1, 1, 2,…
NRLP
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Sklearn clustering gives weird predictions

I have two blobs of points in a 2d plane, which slightly overlap. When I run KMeans fit with 2 clusters, and colour the 2d plane using predictions for each point on the lattice, I get a behaviour that is really different from the original datasets…
Andras Di Giovanni
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How to evaluate how similar 5 datapoints are to 1 target datapoint

I am struggling to wrap my head around a problem I need to resolve. Say that we have a cars dataset (1) with many different cars that have different features (id, age, mileage, color, model,...). On the other hand, we have another dataset (2) with…
naseriani
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Do unsupervised machine learning model features need to be independent?

I'm training an unsupervised machine learning model and want to make sure my features are as useful as possible! Do unsupervised machine learning model featured need to be independent? For example, I have a feature (subscriptionId) that is the…
mangokitty
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Why is SSE an objective function for KMeans++ when decreases with an increase in K

While I do think this to be obvious that, since the distances to the closest centre naturally reduces with an increase in K implying a reduction in SSE with larger K, I was wondering why this is considered an objective function. How can I decide on…
Abhiram Natarajan
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Evaluating the performance of variational autoencoder on unlabeled data

I've designed a variational autoencoder (VAE) that clusters sequential time series data. To evaluate the performance of VAE on labeled data, First, I run KMeans on the raw data and compare the generated labels with the true labels using Adjusted…
ArashV
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Autoencoder for casualty of time series data

I am trying to figure out the link between 2-time series vectors. for example : X = temperature variation for one year; Y = strain measurement for one year; I am new to machine learning. I cannot figure out which unsupervised algorithm to use for…
ImBay
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How to know which features causes anomalies while training isolation forest model

I'm training an unsupersived isolation forest model with a dataframe that contains 10 features , the model performs well and detect anomalies. My question is if an anomaly is catched i want to know which feature(s) has caused that anomaly. Is there…
Bacem
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