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Results tagged with unsupervised-learning
Search options not deleted user 58736
Finding hidden (statistical) structure in unlabelled data, including clustering and feature extraction for dimensionality reduction.
1 vote
Applying and Visualizing k means clustering on a data set that has 9 features
If you want to visualise the data after K-Means, the better approach would be to reduce the dimensionality to two or three dimensions and visualise using a matplotlib 2D or 3D plot. You might also try …
2 votes
2 answers
2k views
How to deal with with rows with zero in every feature while clustering?
I am working on a clustering problem which has 13000 observations and 15 features. Around 3000 observations in the dataset has zero in every features ( i.e all values zero in 3000 rows). I am trying …
3 votes
1 answer
722 views
Does K - Means clustering on data reduced using PCA and the original data make any difference?
I am working on clustering and I have 90 features with 13500 data points and after removing the correlated variables which had pearson correlation more than 90% my feature space reduced to 70. Also, a …
7 votes
4 answers
34k views
How to do feature selection for clustering and implement it in python?
I am trying to implement k-means clustering on 60-70 features and I came across a post for feature selection technique on quora by Julian Ramos, but I fail to understand few steps mentioned. I am als …
5 votes
1 answer
425 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) …
3 votes
3 answers
757 views
What value can I gain by doing exploratory data analysis on features (and thus data) before ...
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 int …