Questions tagged [unsupervised-learning]

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

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19 views

SHAP Kernel explainer for ensemble model

I am currently working on a project involving an unsupervised outlier detection ensemble model. However I am getting stuck by an error passed by the shap.KernelExplainer: "The passed model is not ...
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20 views

2 questions for a project I'm working on about clustering and feature engineering [closed]

Question 1: I have a big dataset where I used Mini Batch KMeans clustering to cluster the dataset into 3 clusters. The thing is that after unsupervised learning, I'm using the distance between the ...
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Why are the Order Of Initial Centroids effecting Kmeans Clustering?

For Iris Dataset I am doing the experiment. iris_k_mean_model_vor = KMeans(n_clusters=3, init=arr_4d) this is my model. Here I am feeding an Initial array of ...
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9 views

Association rule mining for continuous variables

I'm trying to study the relationships between several numerical variables, eg. electricity generation between different stations at 30min intervals over several months. My data has the format I want ...
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8 views

Clustering Ensemble or Consensus to combine the different cluster output

I tried to use ClusterEnsemble, getting error while using ClusterEnsemble package in Python: ...
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14 views

Restricted Boltzmann Machine (RBM) implementation in Tensorflow (TF) 2.x

I‘m looking for a Python implementation of a Restricted Boltzmann Machine (RBM), e.g. applied to MNIST data as mentioned in „Elements of Statistical Learning“ Ch. 17, in Tensorflow 2.x. I‘m aware of ...
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1answer
15 views

Trim left tail of music in audio file

I have audio files, most of them start with the same music, and then a conversation begins. I want to trim the part of the music (which can be varied in length). I have no labels, I can transcribe the ...
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9 views

Two sets of topics/words in Topic Modeling

In short, the question is: I have two sets of words per document. I would like to extract two sets of topics per document corresponding to sets of words. To be more precise: Document(d) can be ...
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1answer
29 views

Clustering text data based on sentiment?

I am scraping reviews off Amazon with the intent to perform sentiment analysis to classify them into positve, negative and neutral. Now the data I would get would be text and unlabeled. My approach to ...
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8 views

How to score different clusters of features for predictiveness?

I have a set of true/false data that represents whether or not a given feature was or was not active when the data snapshot was recorded. Data snapshots are recorded when the user takes an action. The ...
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9 views

How to treat demographic variables in clustering?

I'm working on a project to cluster franchises of a certain company. In this case, the dataset is grouped by city, so I'm basically clustering cities. I'm ending up with variables such as: Population:...
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11 views

Dynamic Clustering - Two States

I wondered if anyone was aware of research and corresponding R packages based upon unsupervised clustering in two different states. For example, suppose I have a panel data sample with 12 ordinal ...
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19 views

Model doesn't know German well enough

I have a model that generates questions and answers based on input text. The texts are in German and based on observations it seems like the model doesn't know German well enough. I need to pretrain ...
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1answer
23 views

Tiering after clustering with Kmeans

I would like to have some suggestions on possible avenues that would make sense in the following context. 3 Optimal clusters have been identified in a 5000 list of customers using Kmeans Data model ...
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1answer
71 views

Machine learning roadmap not for beginners [closed]

To introduce myself: I know what is RL, know some RL algorithms such as PPO, A2C. Know about offline RL, online RL. I have read many papers about RL. Such as MuZero, AplhaZero, Decision Transformer ...
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42 views

Clustering with hierarchical data dependencies

I am currently looking into how to cluster data with hierarchical dependencies. An example of a problem that I want to cluster: we would like to cluster cities to identify similar characteristics with ...
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36 views

Silhouette Score for different Clustering algorithms

I am trying to compare different clustering algorithms on a dataset and compare the model performance. Since the dataset is quite big (56 features), I applied PCA to reduce the number of features to ...
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1answer
22 views

Correct approach to scale (min-max scaler) both input and output signal data for unsupervised learning?

I am working on a denoising autoencoder problem with noisy and clean signals. Before I pass the signals to my model I want to apply min-max normalization and am unsure of the correct way to apply this....
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16 views

what is the best approach for clustering and prediction with dataset having both categorical and numerical columns in python

I have a dataset with survey data asking if people want to buy/have bought certain products. Columns are like: product name survey type/location targeted group, e.g gender, age # of positive answers, ...
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1answer
41 views

Does BERT need supervised data only when fine-tuning?

I've read many articles and papers mentioning how unsupervised training is conducted while pre-training a BERT model. I would like to know if it is possible to fine-tune a BERT model in an ...
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11 views

Find business vertical of a website just by its URL or cluster similar website by its url

I have been exploring this problem a lot about just using the website url to tag or cluster them as per their business domain. For example: ...
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33 views

Question about text classification without labeled data

I am working on a text classifier but at the moment I'm quite lost on what to do. The classes form a tree with three levels, for example, class A (level 1), class A.1 (level 2, subclass of A), and ...
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12 views

Creating a popularity index from multivariate data

I have some data from an ecommerce website with features like product_name, product_category product_link, product_id, free_delivery(1 or 0), price, discount, avg_rating, number of reviews, ...
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22 views

Why is stop-gradient used in Deep Mind's BYOL (Bootstrap Your Own Latent)?

I'm reading Grill's et al. paper regarding their self-supervised approach. I do not understand why the output of the target network is indicated as sg(z'ξ), rather then just (z'ξ), as would seem to ...
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15 views

Is it possible to train a model for sentiment analysis with data that has been labeled with VADER?

I want to perform sentiment analysis on a selection of tweets regarding vaccination. The tweets I find are either unlabeled or have been labeled using VADER or TextBlob. I am wondering if it makes ...
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23 views

How Pretraining part actually work in Wav2vec models? Which data is qualify to be the adequat for fine-tuning part the model of speech2text

Pretraining and fine-tuning the algorithm of wav2vec2.0, the new one using in FAcebookAI to do speech to text for low-resource language. I didn't actually get how the model does the pretraining part ...
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1answer
130 views

Anomaly (Outlier) Detection with Isolation Forest too sensitive even with low contamination

I'm trying to use the sklearn implementation of the Isolation Forest algorithm to detect anomalies in my time series data. However, even with a very low contamination parameter (0.0001), it is ...
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What technique's can be used to identify and count individual animals in a dataset?

Problem: I have an image dataset that contains a lot of different chitals (a species of deer). The images are taken by cameratraps in a National Park. I would like to count the individual animals. For ...
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33 views

Is it possible to cluster unseen data using transductive algorithms like DBSCAN, OPTICS, Spectral Clustering, Agglomerative clustering

I am trying to solve a clustering problem. In general for K-Means clustering we fit the data and whenever we have a new data/sample we use ...
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16 views

Evaluating unsupervised Oulier Detection Models

I'm trying to find ways to evaluate unsupervised outlier detection models like Isolation Forest, One-class SVM, COPOD etc. I found this paper How to Evaluate the Quality of Unsupervised Anomaly ...
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16 views

Statistical method to validate predicted outliers

I was trying to make a clustering-based unsupervised anomaly detection on a large high-dimensional dataset. Roughly saying the points not lied inside all the clusters are defined as anomalies or ...
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42 views

Difference between self supervised learning and unsupervised learning

Self supervised learning is considered a subset of unsupervised learning. Is there any major difference between the two owing to the similarity of self supervised methods towards supervised learning.
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Problems with low silhouette coefficients in unsupervised learning

I created two clustering using k-means clustering. However, two silhouette coefficients are judged to be low. The average silhouette coefficient was about 0.2, the silhouette coefficient for Group A ...
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2answers
60 views

unsupervised anomaly detection for univariate fast frequency time series data?

I have a univariate time series (there is a value for each time sampling) (sampling time: 66.66 micro second, number of samples/sampling time=151) coming from a scala customer This time series ...
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12 views

Predicting categories from data having no targets

I have training data that just contains transaction history of a store which includes user id of the customer, the product purchased and the cost of the purchase. There are repeated transactions from ...
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Clustering dataset with and without estimating means (no EM algorithm)

Given a dataset $D$ of the form $$ D = \{ (x_0,y_0), (x_1,y_1),\ldots,(x_{n},y_n) $$ sampled from a Gaussian mixture model with identity covariance matrices, I want to understand what are my options ...
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64 views

Novelty prediction Using DBSCAN on "unseen data"

I am trying to build an unsupervised learning model, which will be able to predict outliers on "unseen data." The algorithm I chose is DBSCAN (Density-based spatial clustering of ...
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1answer
9 views

Clustering of events

I've a sequence of time ordered set of points: for each $t=1...T$ I have a set of points $(x_{t,i},y_{t,i})$. I need to cluster them together in space-time. I don't know however a priori the number of ...
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2answers
57 views

Can I use labelled data in unsupervised learning algorithms like neural network?

I am working on a transaction dataset that consists of some labeled features like gender, product categories, membership types, and so on. There are also some numeric data like the amount of ...
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16 views

What is the name of this supervised clustering algorithm?

I am doing deep learning research in supervised contrastive learning. The problem I am interested in can be simplified into the below scenario. And I am wondering what is the name of the following ...
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74 views

Using STL(Seasonal-Trend decomposition using LOESS) for Anomaly detection

I am using STL to decompose my time series data in Season, trend and residual and then by applying this(see below) on residual. I am detecting the anomaly ...
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1answer
43 views

How to test unsupervised learning methods for anomaly detection?

How to test unsupervised learning methods for anomaly detection? I am looking for a test strategy to evaluate my result of my anomaly detection technique? what is your offer more than evaluate with ...
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3answers
40 views

How to detect outliers to lable my unsupervised data?

I have unsupervised sensor data and i want to lable each row of data as anomaly or normal. Here K-mean clustering will work?
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1answer
79 views

How to do clustering assuring more than one class per cluster?

I have a dataset with 4 classes and i'm trying to use an ensemble model where each base classifier trains with a portion of data. To distribute data along the classifiers, i am using KMeans algorithm. ...
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1answer
182 views

Clustering on binary data

I am working on clustering on binary data which has 25 features, sample Feature 1 Feature 2 Feature 3 ...... Feature 25 1 1 0 0 011101 1 2 0 1 0 010011 0 3 1 0 1 101001 1 and I have used the ...
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1answer
30 views

Distance between any two points after DBSCAN

DBSCAN is a clustering model which is robust to detect the outliers also. A parameter $\epsilon$ i.e. radius is an input of the algorithm, a point is said to be outlier if it's circle with radius $\...
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2answers
40 views

Real-Time Outlier/Anomaly Detection?

My data is the usage/playing statistics for players of a specific game. One data point for a user is aggregated statistics for one week. The goal is to be able to detect when the account of the player ...
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34 views

Best approach to clustering images

I am new to unsupervised clustering and I wish to perform clustering on a dataset of 512 images. I want to output n clusters where each cluster holds images that are similar to each other. I do not ...
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8 views

Latent Class Output Interpretation

Would appreciate some feedback regarding the output of a latent class model obtained using the 'randomLCA' package. For background, I have six categorical variables: 'MR', 'Mob', 'SC', 'Act' , 'Pain',...
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67 views

Can K-Means cluster label be fixed

Is there any way to fix the K-Means cluster label. I am working with 4 clusters and whenever I run the python program from the beginning the cluster labels change. Is it possible to fix the cluster ...

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