5 votes

Different Meanings of "Clusters" in Statistics

From the Merriam-Webster Dictionary: a number of similar things that occur together The two uses of the term that you describe have to do whether you are trying to discover a cluster in a data set ...
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  • 62.4k
5 votes

Why did Clustering Algorithms Become so Popular Despite their Results often Being "Uninterpretable"?

It is sort of a loaded question to ask why cluster analysis is so popular. This frames cluster analysis as being more popular than it should be. But, you do not explain with specific examples a use of ...
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5 votes

Why did Clustering Algorithms Become so Popular Despite their Results often Being "Uninterpretable"?

Some vague thoughts: "what do observations in the same cluster have in common?" You can take two views of clustering. One is to find groups of data points with attributes that are similar ...
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3 votes
Accepted

Clustering while knowing the ground truth: Why would someone choose this approach?

You would want to cluster instead of classifying when the real-world problems don't share the same categories as the evaluation set you use. For instance, let's say you know the true clusters of a ...
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3 votes

Applications of Dynamic Time Warping (Time Series)

DTW is an algorithm for measuring the distance between two time series. It's an alternative to the Euclidean distance (which is the mean squared distance between the time series at each time step), ...
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  • 496
2 votes

What is the relation between k-means clustering and PCA?

In a recent paper, we found that PCA is able to compress the Euclidean distance of intra-cluster pairs while preserving Euclidean distance of inter-cluster pairs. Notice that K-means aims to minimize ...
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  • 21
2 votes

How can I find the start of a range in an automated way?

Your criterion "the start of the price range where most lots sell" is somewhat vague. In the first region, you pick \$9-10 thousand rather than \$10-11 thousand (presumably because 9-10 is ...
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2 votes
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Distance between two clusters after their joining in centroid linkage

A bit tricky to come up with the manipulations, but let's begin with expanding $d_{i+j,k}$: $$\begin{align}d_{i+j,k}&=||m_{i+j}-m_k||^2=\left|\left|\frac{m_in_i+n_jm_j}{n_i+n_j}-m_k\right|\right|^...
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  • 51.1k
1 vote

RFM Customer segmentation - Why Avg monetary value instead of total monetary value?

The 3 RTM are selected since they are often uncorrelated with each other, but you are free to redefine them or supplement them as you choose. Average revenue is a different metric than total revenue, ...
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1 vote
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1D cluster - Jenks optimization - Finding optimal number

This seems to be a two stage problem: first, identify the number of clusters and then, secondly, optimally perform the clustering. For the first part, I'd suggest Cluster Validation by Prediction ...
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1 vote

Image Clustering (Unsupervised learning) on unknow class(guess less than 300)

The task of having a machine learning algorithm learn how to label unlabeled images is an active area of research. I happen to have two examples handy, but there's a number of alternative approaches. ...
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  • 78.2k
1 vote

How to interpret a PCA score plot?

The content of the interpretation will depend on the interpretation of the two components. Do the groups of variables that load strongly in each component have a coherent meaning? Assuming the two ...
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  • 130
1 vote
Accepted

What variable type to choose for a Poisson distributed variable if software package only allows for nominal, ordinal or continuous

Poisson-distributed data are numeric count data. So a strictly nominal coding, which would treat each count value as a separate unordered level of a multi-level categorical variable, would seem to be ...
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  • 62.4k
1 vote

Can the Response Variable ever be used in Clustering?

The first thing to mention is that the two clusters in your data are very easily separated. This makes it hard to notice differences between approaches to improve the separation between clusters. You ...
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