Linked Questions

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2answers
65 views

Predicting three related scores with one joint model

I have multiple features and I want to predict three outcome scores. Features: Length in cm smallest is 40cm biggest is 209cm Kilo: 39 till 302 Age: 19 till 111 Gender: Male, female, transgender ...
0
votes
2answers
90 views

How to cluster categorical and numerical data in the same dataset?

I have a dataset in which it contains both numerical and categorical data. This can be done using supervised learning algorithms, but I am eager to see how this data can be clustered using some ...
0
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2answers
178 views

KMeans for crime patterns

I'm trying to find the patterns in the crime records I have in a database. I thought clustering would be a way to do it. This is my (cooked up) dataset: ...
1
vote
1answer
39 views

Clustering for Categorical Data? [duplicate]

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 ...
1
vote
1answer
45 views

Clustering with Only Categorical Features

I am trying to do clustering with a bunch (24) of categorical features. I have done some research and found a lot of people recommending something such as K-Modes. I tried running K-Modes on my data ...
1
vote
1answer
26 views

Unsupervised Algorithm for hybrid data [duplicate]

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 ...
1
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1answer
2k views

K-Means clustering for mixed numeric and categorical data implementation in C#

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.
0
votes
1answer
84 views

What is the best way to encode features when clustering data? [duplicate]

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 ...
0
votes
1answer
265 views

Clustering, Mixed Data Set with Ordinal and Nominal Scale Data

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, ...
0
votes
1answer
64 views

clustering with k means

I have dataset with two label class (good and bad), I want to apply K Means on my dataset using python, should I use that label dataset or I have to delete the label class column ?
0
votes
1answer
707 views

Quick start using python and sklearn kmeans?

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 ...
-1
votes
1answer
446 views

Probability of what product will be purchased in repeat orders

I have a problem I need to solve and am looking for assistance in what algorithm to use. I have a online store that I have say 10 products and I have all the order history for every order. What I am ...
-2
votes
1answer
139 views

Apply a clustering algorithm on categorical data with features of multiple values [duplicate]

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 ...
2
votes
0answers
642 views

Mixed geospatial and categorical clustering

I'm working on a project that seeks to identify clusters in urban development based on location (in lat/lon) and a categorical variable (what the particular site is zoned for). Ideally, the analysis ...
1
vote
0answers
46 views

Different approaches for categorical non-ordered data clustering in R

I'm trying to find different clustering approaches for only categorical data in R, so far I found: klaR for kmode cba for rock Hierarchical clustering (agglomerative or divisive) with a categorical ...

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