Questions tagged [categorical-encoding]
The categorical-encoding tag has no usage guidance.
28
questions
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2answers
44 views
Why is count encoding effective in improving accuracy?
Can someone please explain why/how Count encoding of categorical features improve accuracy in classification when compared to simply label encoding them ?
I found one explanation in kaggle " ...
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1answer
56 views
Is this attribute numeric or categorical (ordinal)? Help!
So I have this dataset I need to perform several techniques on as part of a data mining/machine learning project of some sort in PYTHON. There are a couple of features however, that have me very ...
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2answers
19 views
Categorical and non-categorical data in the same column
I have a unique dataset that has many columns and most columns contain both categorical and non-categorical data. For example, let's say that one column is attribute_1 and for observations that have ...
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9 views
Correlation between features in python
I have a dataset which has categorical variables as features. They are nominal in nature. One of the variable has 312 categories. I want to check how correlated the variables are, to check ...
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0answers
7 views
Predict values if will be above a threshold (so bottomline behaviour)
this time I am not asking help with coding but on the concept level. I have trained a classifier (RF but this is not important) that provide goods accuracy (around 90%)
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12 views
Autoencoder to encode features/categories of data
My question is regarding the use of autoencoders (in PyTorch). I have a tabular dataset with a categorical feature that has 10 different categories. Names of these categories are quite different - ...
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1answer
25 views
sklearn serialize label encoder for multiple categorical columns
I have a model with several categorical features that need to be converted to numeric format. I am using a combination of LabelEncoder and OneHotEncoder to achieve this.
Once in production, I need to ...
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1answer
17 views
Categorical data - how to handle
Few questions on categorical data. Need suggestions / pointers:
How can we check for correlation between categorical features and target or between the features themselves?
How about correlation ...
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1answer
33 views
Implementing sklearn's FeatureHasher on Unseen Data
For a little bit of background I have been working on a binary classification of health insurance claims and am implementing sklearn's FeatureHasher to vectorize categorical features, many of which ...
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36 views
Positional Encoding of Categorical Features in a Time Series Transformer
I am training a Transformer for Multivariate Time Series prediction. I am working with Categorical features and I am thinking of using Positional Encoding to encode them instead of Embedding. Has ...
1
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1answer
21 views
Which ML classifier is appropriate for me if all of my features are categorical?
My dataset contains four features. All of the features are categorical. There are 150 categories in the value of 1st and 2nd features. There are 8 categories in the value of 3rd and 4th feature. I ...
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11 views
Best Practices for Boosting, Trees, Random Forests re. Number of classes in a feature and number of samples per class
I'm doing a regression to predict house prices using multiple algorithms and the h2o platform.
In particular, I'm using a variety of GBM, DRF, and GLMs.
I have a large amount of data from several ...
1
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2answers
211 views
what should i do if my target variable is categorical when using decision tree? (many categorical variables)
all,
i'm trying to classify a set of features to belong to a particular company (my dependent variable). my independent variables are a mixture of continuous and categorical features.
my data-set ...
2
votes
1answer
55 views
Categories with the same mean in target encoding
While doing target encoding it can happen that two categories have the same target mean.
This is bad because there will be no difference in the new feature in it and we will lose some information.
...
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0answers
23 views
Implementing Scikit Learn's FeatureHasher for High Cardinality Categorical Data
Background: I am working on a binary classification of health insurance claims. The data I am working with has approximately 1 million rows and a mix of numeric features and categorical features (all ...
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0answers
14 views
Target Encoding and Feature Scaling
I am using Support Vector Classification which performs well when we have done Feature Scaling, however, I am using Target Encoding on my categorical variables. Is it advisable to do Feature Scaling ...
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1answer
33 views
How to do target encoding when data has repeated rows?
How can I do encoding for a category when data has repeated rows? Can I do target encoding? Or Is there another encoding I can use?
I want to figure how to include a categorical variable in a model ...
0
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1answer
49 views
What to do if a specific label of a category appears only a few times?
Let's say I am trying to predict whether a car will be auctioned or not (not what I'm actually trying to do, but it represents it pretty well) using tabular data. I have the year the car was made, its ...
0
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1answer
20 views
What is the best way to encode an arbitrary collection of strings into int categorical variables?
I have a bunch of categorical labels which I want to transform into int categorical features for an ML algorithm.
The problem is I don't have a prior list of the categories, so that I can't just ...
1
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1answer
32 views
Can we optimize regression problems that have categorical variables by encoding them if on the other hand we are inserting multicollinearity? [duplicate]
Can we optimize regression problems that have categorical variables by encoding them if, on the other hand, we are inserting multicollinearity?
2
votes
1answer
18 views
Memory efficient encoding logic for group categories
I have a huge dataset with categorical data. It is comprised of alerts having multiple properties. Each alert belongs to a group, and some even belong to multiple groups. It looks somewhat like this:
...
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0answers
126 views
(Incremental) PCA for all data
I'm using PCA to find prime components that are covering most of the variance in my dataset. What I usually do is I run a PCA for all components, then see how many components cover most of the ...
1
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1answer
18 views
LabelEncoder with a Multi-Layer Perceptron?
So we're working on a machine learning project at work and it's the first time I'm working with an actual team on this. I got pretty good results with a model that uses the following SKLearn pipeline:
...
2
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0answers
47 views
Multi-valued categorical features in LIME
I am working with the LIME implementation by Marco Ribeiro (https://github.com/marcotcr/lime). Specifically, I am utilizing the LimeTabularExplainer as I have a mixture of numerical and categorical ...
2
votes
1answer
24 views
Different encoders applied to a dataset
I have a dataset which have both categorical features with high cardinality (>8000) and low cardinality (4 or 5).
Would that be ok to encode the high cardinality ones with one encoder (target encoder,...
0
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2answers
150 views
Dummy encoding the categorical variables using the changed version of OneHotEncoder [duplicate]
This is my code, I was trying to dummy encode the first column of X using OneHotEncoder but it was showing error and the documentation page of OneHotEncoder says that it has been changed and I wasn't ...
3
votes
1answer
108 views
Strategies to encode categorical variables with many categories
I was going over the Kaggle competitions IEEE,Categorical Feature Encoding Challenge and one of the ways in which categorical variables have been handled is by replacing the variables by the ...
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0answers
47 views
Categorical Encoding with Helmert Coding and James-Stein Encoder
I was going through the coding categorical variables documents and came across the following things:
Helmert Coding
James-Stein Encoder
Can somebody explain the in-detailed implementation of these ...
