Questions tagged [unsupervised-learning]

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

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5
votes
1answer
828 views

Combine two sets of clusters

I have two sets of topics obtained from two different sets of news paper articles. In other words, Cluster_1 = ${x_1, x_2, ..., x_n}$ includes the main topics of 'X' news paper set and Cluster_2 = ${...
1
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0answers
31 views

How can realize the evaluation/validation of unsupervised models through unlabeled data?

I'm researching anomaly detection, which is nothing else than outliers detection on a set of time-series web servers access log data or network traffic. Recently I re-faced to following fundamental ...
24
votes
1answer
26k views

Word2Vec vs. Sentence2Vec vs. Doc2Vec

I recently came across the terms Word2Vec, Sentence2Vec and Doc2Vec and kind of confused as I am new to vector semantics. Can someone please elaborate the differences in these methods in simple words. ...
3
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3answers
83 views

Better approach to assign values to determine potential fake sentences

I am trying to assign different values for each sentences based on information about the presence of hashtags, upper case letters/words (e.g. HATE) and some others. I created a data frame which ...
5
votes
1answer
1k 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 ...
2
votes
1answer
1k views

Estimating Predictive Uncertainty for unlabeled data

I am trying to estimate the predictive uncertainty for a deep neural network. While I do have a labeled training set, I´m trying to measure uncertainty for some unlabeled production data. This paper ...
6
votes
2answers
7k views

Why will the accuracy of a highly unbalanced dataset reduce after oversampling?

I have created a synthetic dataset, with 20 samples in one class and 100 in the other, thus creating an imbalanced dataset. Now the accuracy of classification of the data before balancing is 80% while ...
4
votes
5answers
5k views

Best approach for this unsupervised clustering problem with categorical data?

I'm a software engineer new to Machine Learning. I've read about basic non-supervised techniques like k-means and hierarchical clustering and now I'm trying to put them into practice with a basic ...
2
votes
1answer
1k views

How hidden layer is made binary in Restricted Boltzmann Machine (RBM)?

In RBM, in the positive phase for updating the hidden layer(which should also be binary), [Acually consider a node of h1 ∈ H(hidden layer vector)] to make h1 a binary number we compute the probability ...
8
votes
1answer
749 views

Ideas for prospect scoring model

I have to think about a model to identify prospects (companies) that have a high chance of being converted into clients, and I'm looking for advice on what kind of model could be of use. The ...
5
votes
1answer
102 views

How do I interpret my result of clustering?

I am working on a clustering problem. I have 11 features. My complete data frame has 70-80% zeros. The data had outliers that I capped at 0.5 and 0.95 percentile. However, I tried k-means (python) on ...
3
votes
1answer
168 views

What value can I gain by doing exploratory data analysis on features (and thus data) before doing clustering?

This might not be a very good question, but I would still ask if it's beneficial to do EDA before running a clustering algorithm? I understand that EDA helps us generate good and helpful insights ...
3
votes
4answers
10k views

is it possible to do feature selection for unsupervised machine learning problems?

I started looking for ways to do feature selection in machine learning. By having a quick look at this post , I made the assumption that feature selection is only manageable for supervised learning ...
2
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4answers
80 views

Unsupervised clustering without of Data which is supposed to be on a linear function

When I have a dataset where each datum has x and y, and the (x,y) has a relation of one of <...
1
vote
2answers
30 views

Unsupervised Clustering for n-length word arrays

I have a series of arrays [Apple,Banana,Cherry,Date] [Apple,Fig,Grape] [Banana,Cherry,Date,Elderberry] [Fig,Grape] and I would like to build some clusters that ...