Applied Data Science Coding in Python: Feature Extraction with Univariate Statistics

Hits: 46

Applied Data Science Coding in Python: Feature Extraction with Univariate Statistics

“Feature Extraction with Univariate Statistics” is a technique used in Python to select the most informative features from a dataset. It is based on the statistical tests for the presence of a relationship between each feature and the target variable. The feature selection is based on the statistical test values of each feature and the target variable.

The process starts by calculating the univariate statistical test score of each feature. The scores are then used to rank the features based on their importance. The top-ranking features are then selected and used in the model.

Univariate feature selection can be used with various models such as linear regression, decision trees, and support vector machines. It is a simple and fast method to select features, but it only considers the relationship between each feature and the target variable independently. In contrast, other feature selection methods such as mutual information, consider the mutual relationship between features.

Univariate feature selection is useful for identifying the most important features in a dataset which in turn can be used for further analysis and can also help in reducing the dimensionality of a dataset, which can improve the performance of a model and make it easier to interpret.


In this Applied Machine Learning & Data Science Recipe, the reader will learn: Feature Extraction with Univariate Statistics.

Applied Data Science Coding in Python: Feature Extraction with Univariate Statistics


Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

95% Discount on “Projects & Recipes, tutorials, ebooks”

Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.

Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

There are 2000+ End-to-End Python & R Notebooks are available to build Professional Portfolio as a Data Scientist and/or Machine Learning Specialist. All Notebooks are only $19.95. We would like to request you to have a look at the website for FREE the end-to-end notebooks, and then decide whether you would like to purchase or not.

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!

Visualize Univariate Data – BAR plot in R

Visualize Univariate Data – BOX plot in R