The Functional Data Explorer (FDE) platform is a platform for analyzing functional data, signal data, and time series data. For functional data, you can extract the functional principal components that represent the characteristics and reduce the dimensionality, and perform functions such as discrimination of functional data and creation of predictive models.
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Overview of Functional Data Explorer and Functional Principal Component Analysis (5 minutes 34 seconds)
- For functional data, extracting the functional principal component as a feature of the functional data.
- What will be explained in usage examples 1 and 2, which will be explained later?
Usage example 1: Classifying samples using functional data (16 minutes 52 seconds)
- Basic usage of Function Data Explorer
- How to classify various functions using functional principal components
Usage example 2: Predicting characteristic values using function data (12 minutes 49 seconds)
- Example of extracting functional principal components from functional data and fitting a regression model using the functional principal components as explanatory variables and characteristic values as objective variables.
- Explore the shape of the function that affects the variation in response values.
Usage example 3: Functional response experiment design (11 minutes 27 seconds)
- Example of extracting the function principal component from the function data and using it as a response to examine the relationship with the factor
- Use the Functional Experimental Design Analysis option.
Usage example 4: Analysis of spectrum data (12 minutes 29 seconds)
- Fit a wavelet model to analyze the spectral data.
- Using wavelet experimental design analysis, we investigate the relationship between the shape of the spectrum and various factors.
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