Linked Questions

I need to perform clustering in a given dataset. There are atrributes with numerical as well as categorical values. What is the best way to convert categorical to numeric value ? as an example one ...

Let us I have a people data like gender, age, marital status, education, employment, hobbies. I want to make clusters of those people, having some similarity/common among them (for example they have ...

I have a dataset with numerical and categorical features. I am trying to run a k-means algorithm to find clusters of data. What is the best way to encode categorical features? I have been doing one ...

How exactly does k-means clustering for categorical data work? I have a dataset which has several categorical features that can have 2,3,4,..,n values. I could one hot encode them, but I'm not sure if ...

I have a hybrid data that contains 15 categorical data and 4 continuous data. I need to implement a prediction on the data. So as I don't have any labeled data, I need to implement the unsupervised ...

My data includes survey responses that are binary (numeric) and nominal / categorical. All responses are discrete and at individual level. Data is of shape (n=7219, p=105). Couple things: I am ...

I am clustering data with numeric and categorical variables. To process the categorical variables for the cluster model, I create dummy variables. However, I feel like this results in a higher ...

I have a dataset with categorical features. I want to segment the data using clustering techniques. What could be the possible choices for this scenariogiven the fact that data has categorical ...

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 ...

I have a matrix that is populated with discrete elements, and I need to cluster them (using R) into intact groups. So, for example, take this matrix: ...

I am a research scholar in data mining. I'm interested in C# implementation of K-Means clustering algorithm for mixed numeric and categorical data.

My retail dataset contains 3 numeric attributes and two categorical attributes Time and ID with 50,000 records. Both categorical attributes have more than 20 thousand levels and their format is 1/11/...

I started tinkering with sklearn kmeans last night out of curiosity with the goal of clustering users into groups to see what kind of user groups I can derive. I am lost when it comes to plotting the ...

I have more then 100 columns with the values of 1-0. But the two features at the end as seen in the below image, have different values then the rest. Should I rescale the values in the last two ...

After reading a bit how categorical data can be considered in clustering, I came to the conclusion that most of the post do not make distinction between nominal scale data e.g. colour: red, green, ...