Label Encoding refers to converting categorical labels in a data set used for machine learning purposes, into numeric form. Machine learning algorithms can then decide in a better way on how those labels must be operated. It is an important pre-processing step for a structured data set in supervised learning.
Questions tagged [label-encoding]
119 questions
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Does it make sense to user Standard Scaler after applying Label Encoder?
I'm starting a project on a dataset that contains over 5k unique values for a category.
My question is, after using label encoder, to "enumerate" the categories, does it make sense to use Standard Scaler to make the data a little more "manageable"…
Rafael Duarte
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Can encode categorical data in train set but not in the test set
I need to encode the categorical values on my test set, somehow it throws TypeError: argument must be a string or number. I do not know why this happens because i could do it to my train set. I mean they're train/test feature set so they're exactly…
random student
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For loop in Label encoding and one hot encoder
My Data set contains categorical variables so I am using label encoding and one hot encoder and my code is as follows
can I use a loop to ensure that my code consists of lesser lines of
code?
from sklearn.preprocessing import LabelEncoder,…
Sachin Yadav
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Label encode variable with multiple values
My variable consists of multiple ingredients. Each consists of different ingredients separated by a comma.
I used One Hot Encoding for multiple values(MultiLabelBinarizer()), but it increased my dimension of the dataset.
Do we have some…
DataCat
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LabelEncoder cannot inverse_transform (unseen labels) after imputing missing values
I'm at a beginner to intermediate data science level. I want to impute missing values from a dataframe using knn.
As the dataframe contains strings and floats, I need to encode / decode values using LabelEncoder.
My method is as follows:…
prog-amateur
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2 answers
Encoding Categorical Variables like "State Names"
I have a Categorical column with 'State Names'. I'm unsure about which type of Categorical Encoding I'll have to perform in order to convert them to Numeric type.
There are 83 unique State Names.
Label Encoder is used for ordinal categorical…
Ramya T
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how to maintain natural order when label encoding with scikit learn
I'm trying to fit a model for a decision tree classifier with scikit-learn module. I have 5 features and one of those is categorical, not numerical
from sklearn.tree import DecisionTreeClassifier
from sklearn.preprocessing import LabelEncoder
df =…
Scaramouche
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Error on sklearn --- ValueError: not enough values to unpack (expected 3, got 1)
I am working on an image segmentation problem but I faced this issue. I am trying to create encode labels with multi diminutional array but it need to be flatten, encode and…
Bet
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scikit-learn labelencoder unseen values
uv = np.unique(X[:, 2])
uv2 = np.unique(X_test[:, 2])
print(uv)
#['Female' 'Male']
print(uv2)
#['Female' 'Male']
# Encoding categorical columns in the train dataset
from sklearn.preprocessing import LabelEncoder
labelencoder_X =…
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Label encode then impute missing then inverse encoding
I have a data set on police killings that you can find on Kaggle. There's some missing data in several columns:
UID 0.000000
Name 0.000000
Age 0.018653
Gender 0.000640
Race …
Mario Aguilar
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1 answer
One-Hot Encode & Correlation
I have one-hot encoded a column 'postcode' and I want to see correlation between that and the wealth_segment which has been label encoded as: ( mass customer = 0, affluent customer = 1 and high net worth customer = 2).
I want to see if there is a…
Sana Shah
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How to apply a function to get the encoded specific columns in pandas
I have this function:
get_class(cols):
if cols == 1:
return 1
elif cols ==2:
return 2
else:
return 0
I made a list of certain columns like this:
cols = ['night', 'day']
cols_en = []
for each in cols:
each =…
Ajax
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How to save the true labels I have to encode?
In order to get a Decision tree with sickit learn, I need to Labelencode a dataframe.
S02Q01_Gender S02Q02_Age_rec S02Q03A_Region S02Q03B_Settlement_type S02Q03C_Province S02Q10A_Employment S02Q11_Professional_field Segment…
Revolucion for Monica
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