All Questions
10 questions
2
votes
0
answers
158
views
Normalization/standardization impact on T-SNE and K-means
I have a dataset of 20K samples on 27 features that I am trying to cluster with k-means. The dataset is in its majority rather sparse, i.e. 98% of samples have a single nonzero value in one of its ...
- 21
2
votes
1
answer
460
views
Meaningful to retrieve original value after standardization using clustering
I already referred these posts here and here.
Currently, I am working on customer segmentation using their purchase data.
So, my data has below info for each customer
Based on the above linked posts ...
- 3,342
2
votes
1
answer
925
views
Interpretation of Cluster Distortion on Normalized data
I have a clustering problem which I solved using KMeans clustering. I also know that the Elbow Method for cluster evaluation can be used to approximate a feasible pick for the number of clusters.
I ...
- 143
1
vote
1
answer
3k
views
K-means classifies 96% of my data in 1 cluster. Any suggestions to improve the results?
Problem: K-Means clustering shows 96% of my data belongs to one cluster. How can I improve my results or should I conclude that no cluster exists in my dataset. Dbscan clustering shows 1 cluster ...
- 11
0
votes
1
answer
1k
views
K-means clustering scaling
I have a data set of 70 stores with a sales column (ranging from 50M to 70M) and 39 other features, like age group, income categories etc. I need to find the clusters based off of these metrics.
A ...
- 1
2
votes
1
answer
350
views
Normalization/Standarization for Clustering visualization
I'm performing visualization of a dataset clustered with k-means. I compute a weight for each cluster and I draw a circle as big as its weight. But it seems like after the clustering some values are ...
- 213
1
vote
1
answer
3k
views
normalisation in k means clustering on percentages and other numerical variables
I have several variables to include in k-means, some of them are percentages (between 0-1) and some of them are numerical variables (positive values). I know normalisation is required when the ...
- 13
1
vote
2
answers
2k
views
Use a combination of grand mean and group mean centering to standardize variables
I'm using cluster analysis to examine profiles of three variables, X1, X2, and X3.
Because ...
- 834
1
vote
1
answer
995
views
How to perform Normalization on Call Details Record to perform k-Mean Clustering
I'm new to data mining and currently doing mining project on telecom customer segmentation (based on profile and call details record). I have gender, age, call time and call duration and have to ...
- 135
69
votes
2
answers
100k
views
Are mean normalization and feature scaling needed for k-means clustering?
What are the best (recommended) pre-processing steps before performing k-means?
- 1,373