How Long to Read Grammar-Based Feature Generation for Time-Series Prediction

How Long Does it Take to Read Grammar-Based Feature Generation for Time-Series Prediction?

It takes the average reader 1 hour and 42 minutes to read Grammar-Based Feature Generation for Time-Series Prediction by Anthony Mihirana De Silva

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

Description

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method can be applied to a wide range of machine learning architectures and applications to represent complex feature dependencies explicitly when machine learning cannot achieve this by itself. Industrial applications can use the proposed technique to improve their predictions.

How long is Grammar-Based Feature Generation for Time-Series Prediction?

Grammar-Based Feature Generation for Time-Series Prediction by Anthony Mihirana De Silva is 99 pages long, and a total of 25,641 words.

This makes it 33% the length of the average book. It also has 31% more words than the average book.

How Long Does it Take to Read Grammar-Based Feature Generation for Time-Series Prediction Aloud?

The average oral reading speed is 183 words per minute. This means it takes 2 hours and 20 minutes to read Grammar-Based Feature Generation for Time-Series Prediction aloud.

What Reading Level is Grammar-Based Feature Generation for Time-Series Prediction?

Grammar-Based Feature Generation for Time-Series Prediction is suitable for students ages 10 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 Grammar-Based Feature Generation for Time-Series Prediction?

Grammar-Based Feature Generation for Time-Series Prediction by Anthony Mihirana De Silva 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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