Questions tagged [mixed-type-data]

Dataset including variables of different measurement nature (e.g. continuous, categorical, binary, count etc.) analyzed together in one variable set. Use this tag when this presents a challenge for the analysis. Do NOT use to refer to [mixed-model].

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3 views

Mixed design with continuous between participants measure

Context: I commonly used mixed factorial designs that consist of two of more repeated-measures factors, that participants experience within the same experimental session, and a between-participants ...
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18 views

What is a natural way to define RKHS over mixed spaces (discrete and continuous)?

It is well known that given a kernel $k$ over any space $\mathcal{X}$, there is a corresponding RKHS (Reproducing Kernel Hilbert Space) associated with the kernel $k$. For example, Radial basis ...
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75 views

Louvain Clustering of Iris style Data (in R) [closed]

I have been researching about graph based clustering methods (e.g. Louvain Clustering). I often see examples of graph clustering performed on data with an inherent and underlying graph structure (e.g. ...
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13 views

Categorical x continuous variable interaction in regression?

I have a sample containing two subgroups and I would like to measure the relationship between two continuous variables across the entire group and check if there's an interaction with subgroup. First, ...
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5 views

What is the difference between a factorial analysis for mixed data (FAMD) and a PCA on a dataset where qualitative variable are dummy-encoded?

There are many variants of the principal component analysis (PCA) framework for discrete variables or a mixture of quantitative and discrete variables. Image from this book. However, I am not ...
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17 views

Factor analysis when I have mixture of continuous and dichotomous variables

I am trying to determine if there is a significant difference between two groups for a single continuous variable while accounting for baseline differences in dichotomous variables in each group. To ...
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1answer
44 views

What post-hoc test should be used for a glmer model with a binary response, and a continuous and categorical predictor?

I'm a bit of a newbie with stats and R, so need a bit of direction to find a suitable post-hoc test for my glmer model. I'm trying to find if presence is affected by environmental factors for each ...
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1answer
73 views

PCR after PCA with mixed data - how to extract/export the PCs as new variables in R?

As the title/question implies I ran a PCA with mixed data, i.e. categorical and numeric, in R, once with the "FactoMineR" and "factoextra" packages (analysis version 1) and once with the "PCAmixdata" ...
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11 views

Scaling for mixed data and reverse transform

I have mixed type data (numerical, one hot encoded, ordinal). My data also has outliers. I am trying to scale them using a StandardScaler from sklearn, but I also need to revese transform the test ...
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35 views

Self organized maps on mixed dataset (categoricals / numerics features )

i have a dataset of mixed variables and i want to apply self organized maps on it how can i extend som to mixed dataset? can i use the gower distance instead of euclidienne distance in order to ...
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36 views

How to prove properties about mixed (discrete and continuous inputs) function spaces?

I am using Gaussian Processes for data with mixed inputs (discrete and continuous input variables) i.e. $π‘₯=[π‘₯_𝑐,π‘₯_𝑑]$ where $π‘₯_𝑐 \in \Re$ and $x_d \in \mathbb{Z}$. There is a lot of work on ...
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AUROC and Equality in Scores

The task at hand is to calculate the empirical AUROC for scores assigned to $N + M$ samples from two classes A and B. Most scores lie within the interval (0,1) and are pairwise different, but some ...
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221 views

How to use filter-based feature selection for mixed data types?

The idea behind filter-based methods of feature selection is that we assign a value to each feature, where the value indicates how important the feature is for predicting the outcome variable. We can ...
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8 views

Best way to establish effect sizes in high-dimensional model with mixed data

I have 4 categorical variables, one is by state so it has 50 possible values. I also have 3 continuously distributed values. I'm trying to predict a continuous variable. I'm using a random forest for ...
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1answer
30 views

Two way ANOVA when one independant variable is not Categorical

I am doing a test on doctors' training level and the number on duty. One IV is training level, the other IV is the number of doctors on duty. The DV is the number of patients seen. There are two ...
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1answer
141 views

Mixture model on binary + continuous data

If I have a dataset of continuous variables (that I can assume are normally distributed), I can identify subgroups using a Gaussian mixture model and implement. Likewise if I have binary data I can ...
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22 views

Clustering algorithm for mixed data with non constant categorical variables

I have the following scenario, imagine that I have a dataset as follows: ...
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2answers
84 views

Statistical test to find association between two variables

I'm dealing with ecological data. Broadly speaking, i've counted the plant abundance (discrete variable) in a number of points (small blocks,one number for each ...
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203 views

Input data for Canonical Correspondence Analysis (CCA)

I'm going to conduct Canonical Correspondence Analysis (CCA). In the tutorial I've found at: CCA environmental data are discrete ...
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2answers
80 views

Determination of statistically relevant quantitative/qualitative variables

I have a database containing records of several parameters: one is a quantitative parameter $D$ (e.g. average fuel consumption), others are qualtitative parameters $X_1, ..., X_n$ (e.g. make, color, ...
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70 views

Assessing a binary decission based on continuos and multi-level categorical variables

I have been asked to generate a tool to assess if a particular new set of measurements fit within a list of already accepted ones. The problem is that there are different categorical variables with ...
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132 views

Need PCA or other dimensionality reduction with mixed type variables, before doing clustering

I have a fairly large dataset of 171 mixed variables (104 dichotomous/qualitative, and 67 continuous). My goal is to build a typology of agricultural systems. I originally used a PCA to reduce the ...
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120 views

How to adjust continuous and categorical variables for categorical variable?

I am performing a metaanalysis where I am trying to find predictors for an ordinal response variable. Additionally, I want to perform pair-wise correlations on some of the variables. I have a ...
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1answer
1k views

t-SNE with mixed continuous and binary variables

I am currently investigating the visualisation of high-dimensional data using t-SNE. I have some data with mixed binary and continuous variables and the data appears to cluster the binary data much ...
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1answer
420 views

How to validate clusters after calculating Gower distances and Ward's clustering in R

I am trying to apply Ward's clustering on a mixed types dataset, and wanna explain what I did (maybe helpful to others), and I have some questions regarding this analysis, mainly how to validate my ...
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1answer
76 views

Why does Random Forest not find this simple categorical interaction?

The questions: Why is Random Forest not better at finding an interaction of a simple indicator $\times$ continuous variable? What kind of machine learning model would be better at finding this ...
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1answer
636 views

How to deal with mixed data type in deep neural network?

My dataset has 300 numeric features, each of them ranges from 1 to 500. In addition, I have 1000 categorical features (0 or 1), around 90% are 0's (kind of sparse). To run deep neural network, I ...
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58 views

Using non-parametric transformation (ranking) on variables for factor analysis in R

I have been wrestling with how to simplify a set of mixed variables (some orthogonal, some numeric) some (of both types) of which are significantly skewed. I have run a factor analysis anyway and ...
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17 views

Different conditions on data measurement for ml

Is it possible to train a prediction model (on my case classifier with four classes) between data taken on different conditions? To be more specific I have two data sets and for my task I am allowed ...
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1answer
19 views

How to perform prediction on a mixed type label (i.e. continuous but optional)

I have a set of simulations in which an event may or may not happen. I recorded the time the event occurs and whether it does. I would like to perform regression on the time variable, including ...
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1answer
135 views

Duplicated Rows in Mixed Data Type Clustering

I have a dataset which has ~200k rows and looks like the following - ...
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1answer
96 views

Analysis of impact between 2 observations

I have 2 columns of ~18000 observations. First column contains a value that shows the delay of a filed document (in days) of year 2017. For example: if the document had to be filed on May 5th 2017, ...
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1answer
52 views

Comparing the results of 2 different type but identical samples from 2 devices

I have 2 columns of of the concentration of fat in fish which is measured by 2 different labs. I need to know if the difference of the results from these 2 labs are statistically significant. The data ...
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2answers
588 views

Non-negative matrix factorization (NMF) on mixed data using 1-hot encoding

From a standpoint of interpretation, can I use NMF on one-hot encoded categorical data for dimension reduction? I have mixed data and was thinking about one-hot encoding the categorical features and ...
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89 views

Avoiding multicollinearity with dummy encoding of ordinal variable

I was having trouble finding this exact circumstance; hopefully I haven't missed an obvious previous answer. I have a target variable, Y (discrete counts), and two ...
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36 views

How to compute distances with both categorical and continuous attributes?

I have to handle with a datast containing both categorical attributes (around 25) and continuous attributes (around 25). I would like to do outliers detection. I think that it would be a good idea to ...
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1answer
54 views

Cluster Analysis for mixed data and using a large sample

I wanna perform Cluster Analysis and I have Mixed data (a couple of dummy variables). I've found some information about Gower's distance, but when I tried to use it, R broke down (i guess) because I ...
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2answers
311 views

binary distance k prototype [closed]

I am using k-prototype for my mixed data set. I've chosen Euclidean Distance for my numeric variables; which (dis)similiraty measure can I chose for my categorical variable? The variables ask e.g. for ...
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182 views

How to test for conditional independence with mix of categorical and continuous data

I wish to test for conditional independence between $X$ and $Y$ given $Z$. However $X$ is continuous, while $Y$ and $Z$ are categorical variables. My idea is to test if $P(X|Z = z) = P(X|Y = y, Z = z)...
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1answer
569 views

Is (a) multicollinearity and/or (b) binary variables an issue for DBSCAN? if so, how can one correct for these issues?

I have read some related questions, such as: Why are mixed data a problem for euclidean-based clustering algorithms?, What data structure to use for my cluster analysis or what cluster analysis to use ...
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2answers
2k views

Mixed data in Gaussian Mixture Models

Is it possible to use a dataset with mixed variables such as continuous, ordered, and categorical variables and cluster the data using the Gaussian Mixed Model with EM algorithm. I cannot find ...
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3answers
8k views

Interpreting Silhouette plot for Cluster Analysis

I am running a mixed type data cluster analysis in R and I am trying to interpret the Silhouette Plot. For whatever reason, it is telling me that more clusters is ideal for analysis. Why could this be?...
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1answer
1k views

Difference Between Cubic Clustering Criterion, Silhouette Score, and Calinski Harabasz

I am clustering a mixed geological data set containing numeric (pump pressure, bit speed, mud temperature), nominal (presence or absence of a specific stones), and ordinal data (relative concentration ...
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1answer
351 views

PCA on part of dataset

I have read numerous questions/answers on this site and others debating the use of PCA and other dimensionality reduction techniques on mixed data (containing both continuous and categorical variables)...
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1answer
619 views

How to classify mixed data?

I am trying to do some classification tasks on mixed data set (Hepatitis data set)from UCI ,I will apply SVM and Naive Bayes in R & WEKA, both of them can not handle mixed data directly. Naive ...
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215 views

Number of components in Principal Components Analysis with mixed data

How can I decide about the optimal number of components in Principal component analysis when I have mixed data of of categorical and continuous? I'm using ...
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0answers
1k views

Autoencoder with Mixed Data

Is it reasonable? The categorical features can be binary ("true" or "false") or strings, which are one-hot encoded. Some continuous features may be integers, which are treated as real values. If an ...
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1answer
627 views

Multidimensional similarity space

Does anyone know about multidimensional similarity space? I am working on mixed data set (numerical and categorical), I want to create multidimensional similarity space, contains pairs of similarity ...
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0answers
86 views

Running chi-squared test on mixed data

I have a set of data with high dimension = 80. The set contains mixed features: numerical and categorical data. I'd like to extract all relevant features to an output $Y$ (which is categorical as ...
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1answer
1k views

Can I use Clustering with mixed data type in R? [duplicate]

I know there is same question in cross validated. But it is somewhat different. Clustering of mixed type data with R At there Q&A, as using daisy funtion(), we can use categorical data type in ...