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Feature Engineering: 7 Techniques for Better Predictive Analytics & Machine Learning Models

INTERESTED IN LEARNING ABOUT FEATURE ENGINEERING?

Feature engineering has been a popular concept in the world of data analytics due to its critical role in supporting successful machine learning and predictive analytics. Discover the importance of feature engineering and how you can utilize the process today within your organization across teams and industries.

Download our FREE whitepaper to learn more about feature engineering and how you can successfully apply the seven techniques in Minitab Statistical Software.

Better

Unlock a better, more robust analytics toolkit that will expand your decision-making capabilities, proactively improve your process to achieve better results and avoid costly mistakes with the addition of our predictive analytics tool Classification and Regression Trees (CART). One of the most popular and useful prediction tools, CART is now available in a fast, easy-to-use format within Minitab so you don't need to be a data scientist to use it.

Faster

Assess accuracy of Regression models fast with validation. Effortlessly resample or partition your data into test and training sets with speed, then evaluate your model prediction accuracy faster than ever.

Easier

Unite Python scripts with your Minitab data and analysis easily within Minitab Statistical Software thanks to open-source integration. Capitalize on the ability to expand and further explore your analytical possibilities in the interface or with a macro. Collaborate with data scientists to solve even more problems, all easier with Minitab.

Free White Paper

Feature Engineering: 7 Techniques for Better Predictive Analytics & Machine Learning Models

INTERESTED IN LEARNING ABOUT FEATURE ENGINEERING?

Download Free White Paper

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Powerful Features Make Decision-Making Easier

Better

Faster

Easier

90% of the top Fortune 100 Companies are Minitab Customers