File Exchange

image thumbnail

Multiple order modeling for deep learning

version 1.1 (349 KB) by Mohammad
This is an example of multiple order modeling for accuracy improvement in deep neural networks. Different approaches are shown on how to use

5 Downloads

Updated 13 Aug 2020

View Version History

GitHub view license on GitHub

Introduction
This is an example of multiple order modeling for accuracy improvement in deep neural networks.
Different approaches are shown on how to use the outputs of a category prediction model as predictors for a second model.
Time series instances of samples are used as multiple inputs (for example N frames of a video is used as N image inputs) for model,
and those N number of predicted output (probability density) is used as predictors for the second model.

Data
We attach a set of simulated data for testing this approach.
Details regarding the data is available in comment section of FE_DataLoad.m

Supporting function
A function (trainClassifier.m) attached here for training data with SVM algorithm is called by the scripts.
This function is generated using MATLAB's CalssifierLearner App's code generation functionality

Cite As

Mohammad (2020). Multiple order modeling for deep learning (https://github.com/muquitMW/multiple_order_modeling/releases/tag/1.1), GitHub. Retrieved .

Comments and Ratings (0)

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!