How Long to Read Hands-On Ensemble Learning with R

How Long Does it Take to Read Hands-On Ensemble Learning with R?

It takes the average reader 6 hours and 25 minutes to read Hands-On Ensemble Learning with R by Prabhanjan Narayanachar Tattar

Assuming a reading speed of 250 words per minute. Learn more

Description

Explore powerful R packages to create predictive models using ensemble methods Key Features Implement machine learning algorithms to build ensemble-efficient models Explore powerful R packages to create predictive models using ensemble methods Learn to build ensemble models on large datasets using a practical approach Book Description Ensemble techniques are used for combining two or more similar or dissimilar machine learning algorithms to create a stronger model. Such a model delivers superior prediction power and can give your datasets a boost in accuracy. Hands-On Ensemble Learning with R begins with the important statistical resampling methods. You will then walk through the central trilogy of ensemble techniques – bagging, random forest, and boosting – then you'll learn how they can be used to provide greater accuracy on large datasets using popular R packages. You will learn how to combine model predictions using different machine learning algorithms to build ensemble models. In addition to this, you will explore how to improve the performance of your ensemble models. By the end of this book, you will have learned how machine learning algorithms can be combined to reduce common problems and build simple efficient ensemble models with the help of real-world examples. What you will learn Carry out an essential review of re-sampling methods, bootstrap, and jackknife Explore the key ensemble methods: bagging, random forests, and boosting Use multiple algorithms to make strong predictive models Enjoy a comprehensive treatment of boosting methods Supplement methods with statistical tests, such as ROC Walk through data structures in classification, regression, survival, and time series data Use the supplied R code to implement ensemble methods Learn stacking method to combine heterogeneous machine learning models Who this book is for This book is for you if you are a data scientist or machine learning developer who wants to implement machine learning techniques by building ensemble models with the power of R. You will learn how to combine different machine learning algorithms to perform efficient data processing. Basic knowledge of machine learning techniques and programming knowledge of R would be an added advantage.

How long is Hands-On Ensemble Learning with R?

Hands-On Ensemble Learning with R by Prabhanjan Narayanachar Tattar is 376 pages long, and a total of 96,256 words.

This makes it 127% the length of the average book. It also has 118% more words than the average book.

How Long Does it Take to Read Hands-On Ensemble Learning with R Aloud?

The average oral reading speed is 183 words per minute. This means it takes 8 hours and 45 minutes to read Hands-On Ensemble Learning with R aloud.

What Reading Level is Hands-On Ensemble Learning with R?

Hands-On Ensemble Learning with R is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Hands-On Ensemble Learning with R?

Hands-On Ensemble Learning with R by Prabhanjan Narayanachar Tattar is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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