Analysis of Big Data with Tall Arrays
Statistics and Machine Learning Toolbox™ contains a variety of functions that work with tall arrays. Tall
arrays provide a convenient way to work with data that does not fit in memory, that
is, the sample size can be arbitrarily large. To create a tall array, first create a
datastore that references the data, and then use the
function to convert the datastore into a tall array. For more information about tall
arrays in MATLAB®, see Tall Arrays. For a list of
supported statistics functions, see Function List (Tall Arrays).
If you have Parallel Computing Toolbox™, then the use of parallel computing can speed up certain statistical computations with tall arrays. To use parallel computing with tall arrays, see Extend Tall Arrays with Other Products.
|Scatter plot of bins for tall arrays
- Logistic Regression with Tall Arrays
This example shows how to use logistic regression and other techniques to perform data analysis on tall arrays.