Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [unsupervised-learning]

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

0
votes
0answers
12 views

sklearn & Meanshift for NLP only returns 1 cluster

I am using sklearn.clustering to work with some text data and the MeanShift algorithm. I have: Done all standard NLP data prep like lemmatizing, removing stop ...
1
vote
1answer
34 views

Unsupervised Learning via Supervised Learning

I am interested in exploring some data using unsupervised learning, but I do not wish to limit myself to simple clustering [for example]. Given N features, would it be reasonable to simply run a ...
5
votes
3answers
121 views

Looking for a classification (?) algorithm for linearly separable but unlabeled data points

I have a dataset that is linearly separable with two lines - something like that: Now I'am looking for the right kind of algorithm to do what I guess a SVM would do with labeled data - find the ...
2
votes
1answer
26 views

Using an unsupervised Isolation Forest, how does one identify the optimal number of outliers from the anomaly scores?

I am using an unsupervised isolation forest algorithm and computing anomaly scores to detect outliers from a 2 dimensional toy dataset. From a scatter plot, I am able to detect/visualize the data ...
1
vote
1answer
18 views

How to cluster text-based software requirements

I'm beginner in deep learning and I'd like to cluster text-based software requirements by themes (words similarities/frequency of words) using neural networks. Is there any example/tutorial/github ...
-1
votes
0answers
17 views

graph based clustering with different attributes on vertices and edge proximity

I would like to apply a clustering based approach on a graph oriented problem where vertices do have a set of attributes in addition to another attribute on the edges. The vertices are people and ...
-2
votes
1answer
19 views

Clustering for variables with large amount of categories

I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do ...
0
votes
1answer
35 views

Kmeans clustering with multiple columns containing strings

I have the following dataset: https://www.kaggle.com/carolzhangdc/imdb-5000-movie-dataset What I want to find is clusters based on imdb score per genre per country. I have created a pandas data frame ...
1
vote
1answer
68 views

Simple example of Parzen window (kernel density estimation)

I am confused about the Parzen Window question. Suppose we have two training data points located at 0.5 and 0.7, and we use 0.3 as its rectangle window width. How do we estimate its probability ...
2
votes
1answer
54 views

Unsupervised learning for anomaly detection

I've started working on an anomaly detection in Python. My dataset is a time series one. The data is being collected by some sensors which record and collect data on semiconductor making machines. ...
5
votes
1answer
87 views

How to compare two unsupervised anomaly detection algorithms on the same data-set?

I want to solve an anomaly detection problem on an unlabeled data-set. The only information about this problem is that the anomalies population is lower than 0.1%. It should be notice that the size of ...
1
vote
1answer
54 views

Clustering based on distance between points [closed]

I am trying to cluster geographical locations in such a way that all the locations inside each cluster are at max within 25 miles of each other. For this, I am using Agglomerative clustering. I am ...
1
vote
1answer
31 views

What does Make Density Based Clusterer in Weka do?

In Weka, there is a clustering algorithm with the name as Make Density Based Clusterer. When going through its properties, it takes a clusterer as base clusterer(I took it as K-means with k=3). It ...
2
votes
3answers
74 views

Unsupervised Anomaly Detection on system metrics like memory, cpu, io, net, etc

In all the examples that I can see online, people have used a labelled dataset. I however am stuck trying to construct a model to perform anomaly detection on unlabelled dataset (unsupervised anomaly ...
0
votes
0answers
10 views

Extracting metrics from multiple classes of clustered objects

I am working on a project that involves using object detection over satellite imagery to identify (with bounding boxes) say $k$ different objects [houses, cars, farms, lakes, ...]. By considering the ...
0
votes
0answers
14 views

Where can I find an implementation of an Unsupervised Neural Network?

I'm looking to build from scratch an implementation of the Wake-Sleep algorithm also known as an unsupervised neural network. I plan on doing this in Python in order to better understand how it works. ...
0
votes
1answer
81 views

Anomaly detection on multidimensional time series

I have relatively little knowledge of unsupervised machine learning. I'm working on a project that aims to find anomalies in a set of n data, measured every ...
0
votes
0answers
100 views

How to set the Reconstruction error threshold for anomaly detection using autoencoders?

Hi I am doing anomaly detection using auto encoders.I have trained the model using 'Non Anomalous' values.Now when I give anomalous points as test data. What should be the Reconstruction error ...
2
votes
1answer
33 views

Is splitting the data set into train and validation applicable in unsupervised learning?

I am having a tough time implementing all the steps of setting up support vector machine (SVM) for unsupervised learning. My data set is labelled but for educational purposes I am learning ...
5
votes
1answer
104 views

Gaussian Mixture Models as a classifier?

I'm learning the GMM clustering algorithm. I don't understand how it can used as a classifier. Here are my thought: 1) GMM is an unsupervised ML algorithm. At least that's how ...
-1
votes
1answer
16 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
votes
2answers
53 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
votes
1answer
33 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 ...
1
vote
1answer
19 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
votes
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 $p\ll n$ ...
0
votes
1answer
30 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 ...
1
vote
0answers
18 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
vote
0answers
56 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
votes
1answer
27 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
votes
1answer
33 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 ...
1
vote
3answers
90 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
58 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
43 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 ...
-1
votes
1answer
38 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 ...
1
vote
0answers
53 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
86 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
votes
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
vote
0answers
16 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
votes
2answers
347 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 ...
3
votes
1answer
54 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
votes
1answer
55 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
votes
1answer
39 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
vote
0answers
47 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
36 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
52 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
vote
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
102 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
202 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
38 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
84 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 ...