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
0
votes
0 answers
Subcategories as features
I am using XGbregressor on a dataset with many categorical features. A example looks like this:
shop_name Category Sub-category sub-sub-category revenue
Eateries Resturants Sushi
Eateries …
rohit deraj
- 95
- 6
0
votes
0 answers
SettingWithCopyWarning while using label encoder
from sklearn.preprocessing import LabelEncoder
object_cols = ['Gender', 'Married', 'Dependents', 'Education', 'Self_Employed', 'Credit_History', 'Property_Area', 'Loan_Status']
label_encoder = LabelEncoder()
for col in object_cols:
…
sojc
- 1
0
votes
1 answer
How to override fit() and predict() in a Keras model
I've created a subclass of the keras.models.Sequential class, so that to override the fit() and predict() functions.
My goal is to 'hide' the a sklearn LabelEncoder. This way I can directly call fit() and predict() with a y array made up of…
fortune_pickle
- 141
- 2
- 8
0
votes
1 answer
Label Encoder to Categories
I have created a ML model with Random forest it has 6000+ data with 27 features out of which about 22 were categorical data i have used label encoder on it.Now when i have to predict the result is their a way that when i enter details into as…
Muhammad Minhas
- 1
- 1
0
votes
1 answer
How to do Label encoding in Azure ML studio?
I have a total of around 80 columns out of which some 20 columns are categorical which needs to be label encoded. I checked the solution provided here and the solution stated to work with Feature Hashing technique. But the feature hashing technique…
Sunag
- 105
- 6
0
votes
1 answer
label encoder unable to convert a range of categorical columns into numerical columns
I have a 50 columns, categorical dataset. Among them only 5 columns are numerical. I would like to apply label encoder to make the categorical columns to numerical columns. Categorical columns are basically nominal columns for my dataset. I need to…
Encipher
- 1,370
- 1
- 14
- 31
0
votes
1 answer
label encoding in dask_cudf dataframe
I am trying to use dask_cudf to preprocess a very large dataset (150,000,000+ records) for multi-class xgboost training and am having trouble encoding the class column (dtype is string). I tried using the 'replace' function, but the error message…
0
votes
1 answer
ValueError: y contains previously unseen labels: 'some label'
Whenever i am trying to execute the following code it is showing ValueError: y contains previously unseen labels: 'some_label'
X_test['Gender'] = le.transform(X_test['Gender'])
X_test['Age'] = le.transform(X_test['Age'])
X_test['City_Category'] =…
Nil
- 1
- 1
- 3
0
votes
2 answers
How to apply label encoding uniformly in all columns?
I have a dataset of which I have attached an image.
The set of unique values in Origin and Dest are same. Upon doing label encoding of those columns, I thought that value ATL will get same encoding in 'Origin' and 'Dest' but it turns out that the…
Utkarsh A
- 13
- 1
- 3
0
votes
0 answers
How can i map predicted values (after using RandomForestClassifier) back to their original values in Python?
For context, I am taking Ad listing data for Machines and using it to predict the type of Machine.
I have used the RandomForestClassifier for class prediction. In the model I have used LabelEncoder to convert all categorical variables, including the…
jackyg
- 11
- 1
0
votes
1 answer
sklearn LabelEncoder to combine multiple values into a single label
I am looking to run classification on a column that has few possible values, but i want to consolidate them into fewer labels.
for example, a job may have multiple end states: success, fail, error, killed. but i am looking to classify the jobs into…
Ehud Kaldor
- 753
- 1
- 7
- 20
0
votes
1 answer
LabelEncoding large amounts of categorical data
I have a dataset with 39 categorical and 27 numerical features. I am trying to encode the categorical data and need to be able to inverse transform and call transform for each column again. Is there a prettier way of doing it than defining 39…
Tom_Scott
- 95
- 7
0
votes
1 answer
A function for onehotencoding and labelencoding in a dataframe
I keep getting AttributeError: 'DataFrame' object has no attribute 'column' when I run the function on a column in a dataframe
def reform (column, dataframe):
if dataframe.column.nunique() > 2 and dataframe.column.dtypes == object:
…
0
votes
0 answers
scikit learn label encoding prints as row instead of column
I am trying to do label encoding using sci kit learn's built in function but why does my result print as row instead of an additional column?
from sklearn.preprocessing import LabelEncoder
# creating instance of labelencoder
labelencoder =…
odebear
- 69
- 1
- 8
0
votes
1 answer
What is the the good way to proceed with LabelEncoder with sklearn to get back the coulples?
I have a dataframe with categorical value like city name for instance.
For ML algo., I need then encode the data into numerical value.
I do it like this:
df[cat_columns] = df[cat_columns].apply(preprocessing.LabelEncoder().fit_transform)
My…
pacdev
- 551
- 1
- 3
- 13