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Questions tagged [unsupervised-learning]

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

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1answer
12 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 : ...
2
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2answers
48 views

Grouping already clustered data (with a pre-defined x and y)

I have an already clustered data set (I wanna keep my x and y), where there's clearly a small group of elements in the middle that don't follow the expected patterns. I can select them manually, but ...
0
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1answer
22 views

Unsupervised Learning and Training Data

As far as I know, we need to use training data to find out the relation between the features, also known as input values, and labels, that are output values, in supervised learning. After that, by ...
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1answer
18 views

Supervised or unsupervised learning for predicting energy consumption for new buildings

I’m working on an model for auto dimensioning district heating pipes for new district heating areas (new customers). I have energy consumption data on hourly basis and describe data about these ...
0
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0answers
9 views

Finding features vector to distinguish different shapes in a plane

I have a set of points in a plane where is each set correspond to a particular geometric shape. I need to find a feature vector which can be used to distinguish these shapes. The shapes in the plane ...
0
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0answers
7 views

What methods exist for recommendation based on implicit information?

Assume we have a dataset of which products a user is using on a monthly basis. Let's further assume that the number of users is $n$ and the number of products is $p$ and that we are in the $p\ll n$ ...
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0answers
12 views

Are ReLUs used for training deep Boltzmann machines (DBMs) in an unsupervised setting?

Sigmoid activations follow naturally from the definition of Boltzmann distributions. I understand that for supervised tasks, ReLUs are now commonly used because of better performance/no exploding/...
0
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1answer
27 views

Gibbs sampling (For inference) vs EM

I'm familiar with the Expectation-Maximixation algorithm and, until now, I thought it was the only way to maximize the likelihood of the observed data, assuming a Gaussian mixture model. In the last ...
0
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0answers
20 views

Unsupervised approach to News website pages classification in 3 classes

I'm working on a project in which we have to classify web pages, coming from a news website, into 3 main classes: Sections (or Categories), News and Others (like contact pages, "about us" etc.). We ...
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0answers
14 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 ...
1
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0answers
37 views

PCA for unsupervised feature selection [closed]

If I understood correctly, "using results of PCA to select features" (as recommended in this answer) implies visually analysing bi-plots of first two principal components - i.e. the angle between a ...
0
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1answer
18 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 ...
0
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1answer
29 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 ...
0
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0answers
11 views

Evaluating Performance of Unsupervised Learning Algorithm

I'm trying to match two Documents using Doc2Vec Algorithm And so far it is giving satisfactory results, However I'm unable to know if my model is improving or not. I'm now stuck in the thought process ...
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0answers
11 views

Unsupervised learning use cases for relational data

Most of the unsupervised learning use cases I've previously worked on dealt exclusively with unstructured (text) data - topic modeling and general clustering approaches basically for easier document ...
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3answers
64 views

How to create clusters based on sentence similarity?

I have data which looks like following. Data is a group of sentences which are similar, but have few unique words in between like TABLEA, TABLEB etc. ...
2
votes
3answers
45 views

ML algorithm for Music Features

I am a newbie in machine learning topic and I need to create model from music data. It contains features of the songs but it is not labeled. How can I create a model from that ? Do I need to use ...
0
votes
1answer
36 views

Unsupervised learning from images [closed]

I want to design a model that can detect the different feature in the images, let's consider we have ~100000 images of cows. when I give this images to the model it has to identify different parts of ...
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1answer
22 views

Clustering Customers on transactional behavior

Objective: Segment the accounts on their transactional behavior and find the accounts which are more likely to subscribe for loans. Dataset: 1) Account_Number 2-91) Transaction amount ...
0
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0answers
22 views

python - How do I extract the id from an unsupervised text classification

So I have the following dataframe: id text 342 text sample 341 another text sample 343 ... And the following code: ...
1
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0answers
23 views

Training detector without bounding box data

From what I can see most object detection NNs (Fast(er) R-CNN, YOLO etc) are trained on data including bounding boxes indicating where in the picture the objects are localized. Is there any model ...
0
votes
1answer
54 views

How can I detect anomalies/outliers in my online streaming data on a real-time basis?

Say, I've a huge set of data(infinite in size) consisting of alternating sine wave and step pulses one after the other. What I want from my model is to parse the data sequence wise or point wise and ...
0
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1answer
18 views

Working with few instances of specific target feature over large dataset

I have data over a single, a machine includes different components, all the parts are interacting, the data are tracked for those parts, it tracks power consumption and many other relevant feature ...
1
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0answers
14 views

TextRank algorithm for Web content

I am looking for an algorithm that would be able to extract meaningful keyphrases from web articles. Each article has more than 2000 words and information is structured using paragraphs, h1, h2 tags ...
4
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2answers
305 views

Is SVD non-linear while PCA (by eigendecompostion) is linear?

I am quite confused because a colleague of mine recently told me that he preferred using SVD instead of PCA (by eigendecomposition) because, contrary to the latter, the former is non-linear so it can ...
2
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1answer
50 views

Is PCA (by eigendecomposition) or SVD better in decorrelating the predictors of a machine learning model?

Is there any reason to think that SVD is better than PCA (by eigendecomposition) in decorrelating the predictors of a machine learning model?
0
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1answer
50 views

how to build a predictive model without training data neither historical data

I m trying to score "how much a product is expected in the market". I created some features: How much this product is used each year. Where was it used . how many product for each country. the main ...
0
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1answer
38 views

Is there an upper bound for k in nearest neighbors-based methods?

When applying a nearest neighbors-based method to a data of, for instance, 2000 points, what is the largest number of neighbors that can be considered ? I am using a nearest neighbors method in an ...
1
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0answers
41 views

Time-series clustering Quality Measures

I am clustering time-series datasets which are not labeled (No Ground truth) and I want to measure the quality of the clusters. Could you please suggest any Clustering performance evaluation methods ...
1
vote
1answer
33 views

Is train/test-Split in unsupervised learning of neural network necessary?

I am using autoencoder for anomaly detection in warranty data. It is unsupervised. I calculate the reconstruction error by the model and the records with high reconstruction error value is considered ...
-1
votes
1answer
38 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 ...
1
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0answers
18 views

Decision tree to get difference in rates in two groups?

I have two sample groups of customers, each customer has 100s of features. For a single sample, i would use Decision Trees to find sub-groups that have a high churn rate. Thats easy. However, my ...
1
vote
1answer
73 views

More weightage to a categorical feature for an Autoencoder model

I am using autoencoder for anomaly detection. I don't have any labels already and so its unsupervised. If I have categorical variables, I usually one hot encode before giving it to the model. I would ...
2
votes
1answer
114 views

ML Models: How to handle categorical feature with over 1000 unique values

I am trying to build an ML Classification model on a data set that contains quite a few categorical columns. However, few of them have over 1000 unique values. I am concerned that if I run one-hot ...
0
votes
1answer
31 views

How to split temporal sequences to sub-sequences in a meaningful yet unsupervised manner?

I have a biological process that undergoes some cellular event which I am observing. I have a series of events, with different temporal gaps between them. For example ...
3
votes
1answer
65 views

How to use a different model to deep neural network with reinforcement learning based on DQN?

Is it possible to implement a reinforcement learning algorithm without using a deep neural network (DNN) as used in deep reinforcement learning e.g. Deep Q-Network (DQN)? How can I replace the DNN in ...
2
votes
1answer
36 views

Given data that is labeled as outliers, how can I classify data as outliers?

I have a dataset that is a mixture of sparse binary features and quantitative features. I only have definite outliers labeled. How should I approach trying to classify unlabeled data? I considered ...
2
votes
2answers
4k views

Anomaly detection on time series

I've just started to working on an anomaly detection development in Python. My data sets regard a collection of timeseries. More in details, data are coming from some sensors/meters which record and ...
1
vote
2answers
163 views

Cross validation for anomaly detection using autoencoder

I am using autoencoder for anomaly detection in warranty data. I don't have any ground truth labels to confirm whether the anomalies detected by the model is really an anomaly or not. Since I don't ...
0
votes
1answer
234 views

using unsupervised learning algorithms on images

I am working on a project to classify images of types of cloth (shirt, tshirt, pant etc). While this is a standard supervised classification problem, the accuracy of the neural network is not good. ...
5
votes
1answer
101 views

What does it mean by “t-SNE retains the structure of the data”?

I was learning about t-SNE when I was told that t-SNE retains the structure of the data in the embeddings. What exactly does this mean ? How does the algorithm achieve this ? So far I have ...
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2answers
45 views

How to identify clusters after multiple runs?

Suppose I run an unsupervised clustering algorithm. After multiple runs, I find clusters and would like to know if the same cluster was found more than once. For example: I can figure out A-orange, ...
1
vote
0answers
26 views

Semi-supervised Learning doubt

I'm reading "Hands on machine learning" by Aurelien Geron. He stated that semi-supervised learning is: Some photo-hosting services, such as Google Photos, are good examples of this. Once you ...
0
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0answers
37 views

Strategies for better temporal learning

The network in question has 2 non-input layers (hidden and output). Forward pass: ...
0
votes
2answers
195 views

What machine learning algorithms to use for unsupervised POS tagging?

I am interested in an unsupervised approach to training a POS-tagger. Labeling is very difficult and I would like to test a tagger for my specific domain, chats, where users typically write in lower ...
1
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0answers
23 views

Classifying variable types on a list of variables

I have a list of around 700 variables which I need to perform a variable cleanup on. What complicates things is there are different numeric codes which flag an invalid value and these differ by the ...
1
vote
0answers
36 views

Random Training set for GAN's [closed]

I have studies the gans in depth and some of its type like cycle, pix2pix, cgans. Now I want to generate random images from random distribution from generator. So I am creating a dataset with no ...
-1
votes
1answer
35 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 ...
1
vote
1answer
149 views

Graph & Network Mining: clustering/community detection/ classification

I am working on graphs/networks where nodes and edges have some attributes. I want to know what algorithm exist for: 1) clustering a graph to k groups: depend only on the structure (edge attribute ...
0
votes
1answer
335 views

Chat Bot Answering based on Data Corpus Self-Training

I have created a very simple chat bot based on RASA NLU. In this case, I manually create some sample input text and create a model for using it against unknown source of input. It's fine for now. As ...