Encoding Techniques for Machine Learning | Data Preprocessing

Показать описание

Categorical Value
Label Encoding
One Hot Encoding
Dummy Encoding
Hash Encoding
Binary Encoding
Data Preprocessing
Data Preparation

Рекомендации по теме

Комментарии

Easy to understand. That was a great teaching Mam. Do more videos on Data Science and Analysis mam. Thank you.

nextdoortechieaminfirnash

Thank you maam for this wonderful video.

br

Hi Suganya 😊
! Thank you so much for this super clear and useful video!

About nominal categorical feature selection (e.g. using Chi2, Cramers’ V, Boruta) and regularization (e.g. using Lasso, Ridge), which encoding should be used ?

My problem is that nominal categorical features used to be encoded using OneHotEncoding, Dummy encoding, etc. However, once they have been encoded, we have ‘new features’. For instance, the column ‘Animal’, with values ‘dog’, ‘cat’ and ‘mouse’… after OneHotEncoding it will be represented with three ‘new columns’ (a column with the name of each animal) ‘col_dog’, ‘col_cat’, ‘col_mouse’, and with values 0 or 1. So, it is not pertinent to apply feature selection on these ‘new columns’, neither regularization, right?

On the other hand with Label encoding we will keep the single original column, but this encoding is for ordinal categorical features right? So not applied in our example dog, cat, mouse since there is no notion of order among them.
So… what should be done in this case?

Thank you very much in advance for your very kind answer!

lourdesmartinez

# create object of Ordinalencoding
encoder= ce.OrdinalEncoder(cols=['Degree'], return_df=True,
mapping=[{'col':'Degree', 'mapping':{'None':0, 'School':1, 'Diploma':2, 'Bachelors':3, 'Masters':4, 'Phd':5}}])
df = encoder.fit_transform(df)

saitarun

this is the code for the label encoding but you wrote ordinal encoding code for label encoding

# Import label encoder
from sklearn import preprocessing
# label_encoder object knows how to understand word labels.
label_encoder = preprocessing.LabelEncoder()
# Encode labels in column 'Country'.
df['Country']=
df

saitarun

Encoding Techniques for Machine Learning | Data Preprocessing

One-Hot, Label, Target and K-Fold Target Encoding, Clearly Explained!!!

Quick explanation: One-hot encoding

Different Types of Feature Engineering Encoding Techniques

7. Different Encoding Techniques | ML Concepts

Encoding Categorical Data | Ordinal Encoding | Label Encoding

Encoding | Feature Engineering Encoding Techniques | Machine Learning

Encoding techniques for machine learning data preprocessing

Feature Encoding in ML: Beyond the Basics

Comparison with Traditional Positional Encodings ##ai ##artificialintelligence ##machinelearning

Machine Learning Tutorial Python - 6: Dummy Variables & One Hot Encoding

Data Encoding methods in Machine Learning #tutorial #encoding #machinelearning #python

Categorical Variables Encoding Techniques | Part -1 | Machine Learning

One Hot Encoding Vs Label Encoding Explained with Example in Hindi l Machine Learning Course

Quick understanding of One-hot encoding Technique in Machine learning modelling.

Encoding Techniques for Machine Learning | Data Preprocessing

One Hot Encoding | Handling Categorical Data | Day 27 | 100 Days of Machine Learning

Feature Encoding 101: Prepare Data For Machine Learning

Feature Encoding Techniques Machine Learning

39. Comprehensive Guide to Encoding Techniques in Machine Learning 🔢🔍

Binary encoding - Encoding Techniques in Machine Learning - Python

What is one-hot encoding?

Variable Encoding in Machine Learning

Unlocking Data Magic Mastering Encoding Techniques for Machine Learning! 🔍

Encoding classical data in a quantum computer