All Questions
Tagged with k-means standardization
16 questions
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Mathematics behind standardizing the data points in machine learning algorithms (e.g., K-means clustering)
For K-means algorithm, among other methods using distance-based measurements to determine similarity between data points, why we have to standardize the data points with mean as 0 and standard ...
- 121
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31
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How to interpret the Scatter Plot result from PCA? [duplicate]
I have a project in school about clustering analysis. I have applied standardization and principal component analysis (PCA) to my dataset (I used K-means), which is about heart disease patients. I ...
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2
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159
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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 ...
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Difference between Log Transformation and Standardization
Is there any difference between the log transformation and standardization of data before subjecting the data to a machine learning algorithm (say k-means clustering)?
It looks like a common approach ...
- 375
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k-means and (re?) standardisation of a sub-set
I have data which is customer purchases of items in each of three months:
I have summed the data over the three months for each customer;
calculated the proportion of purchases that each item ...
- 227
4
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8k
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In cluster analysis should I scale (standardize) my data if variables are in the same units?
I am performing cluster analysis (k-means and hierarchical) based on multiple variables. Each variable is in percentage 0-100% and the sum of all variables is at most 100%.
I see that in many of the ...
- 279
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1k
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Standardizing Percentages and raw data
Apologies for what looks like a easy question but i'm a doing a geodemogrpahic classification and i'm about to run my cluster analysis. Most of my data is in percentages (ie %black,white,asian etc) ...
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Steps of a clustering problems composed by right-skewed data and large number of zeros
I'm trying to cluster a dataset based on 190 diabetic patients and 20 columns (features of patients) and many of these features have most zeros (to understand better, the median of 8 of 20 features is ...
- 21
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194
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K-means clustering: is data set standardization strongly advised? [duplicate]
Let a data set like this:
...
- 637
2
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1
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350
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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
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3
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4k
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Standardizing some features in K-Means
I have 21 features in my dataset, some features are more important than others. As a fact I know, if I don't standardize (mean=0, SD=1) any features, then features with low variance will have slightly ...
- 121
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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
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152
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Standardizing variables for k-means?
I only have two variables and they are on the same scale. However, the variance corresponding to the first variable is approximately 0.609, whereas for the second variable is 0.154. So my question is ...
- 111
2
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1
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920
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Interpreting standardized mean centers in a cluster
I created a $k$-means with 3 clusters. Some of the variables had a big scale, so I used a $z$-score to standardize them. The others (mostly dummies), I left as is.
Now, when I create the table of all ...
- 623
1
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Should I standardize my variables for this particular case of cluster analysis?
I'm trying to cluster a list of records based on a (percentage) frequency distribution of variables which add up to 100%.
Like
Record1 - VarA(25%) VarB(25%) varC(50%) varD(0%)
Record2- VarA(50%) ...
- 11
2
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0
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457
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Standardizing non-normal data for use in distance-based classifier
I have a dataset containing non-normally distributed variables that I want to feed into a distance-based classifier (e.g. K-means). Is it ok to just subtract the mean and divide by the standard ...
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