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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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Self organizing Maps and Linear vector quantization

Self organizing maps are more suited for clustering(dimension reduction) rather than classification. But SOM's are used in Linear vector quantization for fine tuning. But LVQ is a supervised leaning method. So to use SOM's in LVQ, LVQ should be…
clarkson
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why unsupervised model needs to implement nn.diag?

I am trying to learn deep learning. In torch tutorial, https://github.com/torch/tutorials/blob/master/2_supervised/2_model.lua https://github.com/torch/tutorials/blob/master/3_unsupervised/2_models.lua Supervised model -- Simple 2-layer neural…
yutseho
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New Python Install; Scripts Running very Slow

Current Python Version 2.7.10 - I have tried a straight download from python.org and the Anaconda distribution. Previous Python Version was 2.7.x (don't remember) - I know it was an Enthought Canopy distribution. I just 'upgraded' windows from 7…
TommyD
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calculating similarity between two profiles for number of common features

I am working on a clustering problem of social network profiles and each profile document is represented by number of times the 'term of interest occurs' in the profile description. To do clustering effectively, I am trying to find the correct…
Yantraguru
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Learning approach to deciding which UI to present

This application has it's roots in public transport. Users opening the application and looking at the departure times of buses for specific stops (page 1) or planning a journey from location A to B with a journey planner(page 2). Two separate pages,…
basickarl
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How to compute accuracy for cluster evaluation in Weka

How do we compute accuracy for clusters using Weka? I can use this formula: Accuracy (A) = (tp+tn)/Total # samples but how can I know what is the true positive, false positive, true negative and false negative in the output of experiment in the…
Fahad Gh
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unsupervised random forest classification of raster stack in R

I want to compute an unsupervised random forest classification out of a raster stack in R. The raster stack represents the same extent in different spectral bands and as a result I want to obtain an unsupervised classification of the stack. I am…
user2978751
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Why only hyperplanes in support-vector machines?

I only recently learnt about support vector machines. From what I understood, hyperplanes are used to separate the data (raised to the higher dimension) into two mutually exclusive parts (partitions). My question is why should it be a hyperplane and…
damith219
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Unsupervised Clustering with Haskell

I'm trying to develop an algorithm that can report the frequency and closeness in which similar patterns appear between data sets. Simple example: set1 = [0, 1, 0, 0, 2, 0, 0, 3, 0] set2 = [1, 2, 3, 0, 0, 0, 0, 0, 0] set3 = [0, 0, 0, 0, 0, 1, 2, 0,…
subtlearray
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Unsupervised classification - feature vectors are obtained

I need to classify commercial products. You know what price comparison engines does. We have obtained the feature vectors. They are not the best yet pretty good. My last step is classifying them without knowing how many clusters there are. So…
Furkan Gözükara
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Debugging the implementation of Baum Welch Algorithm (for POS tagging)

I am working on a project, a part of which is to develop an unsupervised HMM trainer for POS tagging, which I now want to test for posible bugs. I am using Baum-Welch algorithm to train the model. The inputs are sequence words (drawn from a corpus)…
Irtiza
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ValueError: Buffer dtype mismatch, expected 'double_t' but got 'float' - hdbscan validity_index

I'm using the validity index in the hdbscan package, which implements DBCV score according to the following paper: https://www.dbs.ifi.lmu.de/~zimek/publications/SDM2014/DBCV.pdf I'm working on a face clustering project, and after using the validity…
Faisal Aldhuwayhi
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How can I do unsupervised learning with LSTM in tensorflow (Keras)?

I am trying to use UNSW-NB15 to train a model. After the model is trained, I would like to use the model on live network data. I began creating this using a supervised LSTM but started wondering about handling the data from the network and the…
Alvinus Melius
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How do I completely ignore labels when using Keras image_dataset_from_directory?

When trying to load my image dataset for an unsupervised problem, without labels, the image_dataset_from_directory function from Keras assumes they belong to a class. The resulting dataset has shape: (batch_size, None, image_height, image_width,…
HMUNACHI
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Stacking ensemble of classifiers in a chain

I have the following human activity recognition sample dataset: df = pd.DataFrame( { 'mean_speed': [40.01, 3.1, 2.88, 20.89, 5.82, 40.01, 33.1, 40.88, 20.89, 5.82, 40.018, 23.1], 'max_speed': [70.11, 6.71, 7.08, 39.63, 6.68, 70.11, 65.71,…
arilwan
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