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Questions tagged [dummy-variables]

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43 views

Problem with converting string to dummy variables

I'm new in data science, I have data which want to work on it, I omitted extra columns and convert it to 4 columns ( Product, Date, Market, Demand ) . in this data Product and Market are string, I ...
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1answer
17 views

How to handle fixed values for variables in pre-processing

I have a dataset which contains few variables whose values do not change. Some of the variables are non-numeric (for example all values for that variable contain the value 5) and few variables are ...
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2answers
26 views

Pandas get_dummies() rows dropping after joining back with X

I'm having an issue that I can't explain and am hoping I am missing something simple. I have a large dataset of shape(45Million+, 51) and am loading it in for some analyses (classifiers, deep learning,...
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1answer
23 views

onehotencoder random forest

In a Random Forest context, do I need to setup dummies/OnehotEncoder in a dataset where features/varibles are numerical but refer to some kind of category? Let's say I have the following variables: ...
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1answer
35 views

Creating dummy variables [closed]

I have a Eurobarometer dataset and want to eventually create a logistic regression model and a linear probability model using a set of dates as the dependent variable. However, the dates in the ...
2
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1answer
21 views

Dummy variable only for character value in a column (Neglecting float and integers)

My dataset consists of 3000 rows and 50 columns, out of which one column (ESTIMATE_FAMILY_CONTRIBUTION) contains all numerical value(around 2000 different values like 20,30,32....) but got one value ...
1
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1answer
22 views

Random Forest in R with only character variables

I am new to using random forest in R an my goal is to identify the independent variables which have the highest impact on the dependent variables. I am looking at sales data, and sales is my dependent ...
1
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1answer
32 views

Handling Numerical Categorical Column in ML models in Python

When I was exploring the titanic dataset to estimate the probability of a person of surviving using the Logistic Model, I realized there are two ways of handling numerical categorical variables : Use ...
2
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1answer
530 views

How to interpret dummy variable in ML prediction?

I am working on a binary classification problem where I have a mix of continuous and categorical variables. Categorical variables were created by me using ...
1
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2answers
162 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 ...
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1answer
52 views

Create new variable in python for each iteration

I have two different dataframes like below. And I need to make a dataframe like the following one. Can you please help on how to that in python? Thanks
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3answers
199 views

How to handle “year” variable for Machine Learning models

I have a "year" variable but I don't know which is the best way to handle it for a ML model, as it is a numerical variable, giving some sequence. Should I treat it as a categorical variable? Thanks ...
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1answer
23 views

Frequency of occurrence - dummy variables

I am thinking about it not the first time, namely if I have a variable that I want to convert later to the variable dummy (cities in this case), should I delete lines that occur less often than N ...
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2answers
112 views

How to Keep Missing Values in Ordinal Logistic Regression

I’m using mord package in python to do ordinal logit regression (predict response to movie rating 1-5 stars). One of my predictor variables is also ordinal but ...
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0answers
39 views

Same coefficient in multivariate regression with dummy variables

Hello Data Science community, I have a model with 1 quantitative variable (y) and 2 categorical variables. In order to work with the categorical variables I have created dummy variables (binary) for ...
1
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1answer
17 views

Handling hierarchical category independent variables

I have data with huge categorical attributes. For example, main_column, sub_column1, sub_column2 are 3 hierarchical attributes. If if take dummy variable on these columns the column count is ...
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2answers
2k views

Prediction after one hot encoding

I have a regression model that I want to make prediction based on values that I will get from an end user. In my dataset, I have one categorical variable region ...
3
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3answers
3k views

Obtaining consistent one-hot encoding of train / production data

I'm building an app that will require user input. Currently, on the training set, I run the following code, in which data is a pandas dataframe with a combination ...
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1answer
239 views

convert keywords in one column into several dummy columns

My dataframe has some free text fields named: {'title', 'description', 'location'} I prepared this text column by: concatenating all into a new column, dropping ...
6
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3answers
551 views

How to give a higher importance to certain features in a (k-means) clustering model?

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 ...
1
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1answer
125 views

How Dummy Variables Should Be Modeled In A Linear Regression Model?

I've a cross sectional model where I want predict number of users that take specific service, to make it I've many variables but have specifically two nominal: isWorkday(0 or 1) and weeday(1,2,3,...,7)...
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1answer
78 views

caret dummyVars on unseen data

I created my dummy variables, trained my model and tested it as below: ...
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0answers
85 views

How to deal with a potencially multiple categorical variable

I'm build a model that has, as inputs, some categorical variables. I had already dealt with this sort of data before, and applied different techniques as creation of dummy variables and factor scoring....
1
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1answer
126 views

Can you apply PCA to part of your dataset?

I am working with kaggle dataset that has over 130 features composed of 116 categorical and 14 continuous features. I plotted the heatmap for the 14 continuous variables and found that most of them ...
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2answers
2k views

In which cases shouldn't we drop the first level of categorical variables?

Beginner in machine learning, I'm looking into the one-hot encoding concept. Unlike in statistics when you always want to drop the first level to have k-1 dummies (...
3
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1answer
2k views

Using pandas get_dummies() on real world unseen data

I made a ML model, trained and tested it with my data containing categorical variables. To create dummy variables I used pd.get_dummies() before the split. I now ...
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0answers
64 views

Dummy variables for unseen data in R

I got the following problem: When I trained my model I created my dummy variables(before train-test split) in the following way: ...
3
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3answers
691 views

How to obtain original feature names after using one-hot encoding

This question is on an implementation aspect of sklearn DecisionTreeClassifier How do I get the feature names ranked in descending order, from the feature_importances_ returned by the sklearn ...