Training Neural Network for classification
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I'm working on gait recognition problem, the aim of this study is to be used for user authentication
I have data of 36 users
I've successfully extracted features which are (36 rows and 143 columns) for each user
( by the way, column represents the number of the extracted features and row represents the number of samples for each feature).
Then I have divided the data into two parts, training and testing ( the training matrix contains 25 rows and 143 columns, while the testing Matrix contains 11 rows and 143 columns).
I'm new to classification and this stuff,
I'd like to use machine learning (Neural Network) for classifying these features.
Therefore, the first step I need to create a reference template for each user ( which called training phase)
this can be done by training the classifier with the user's features (data) and the imposter's data as well (35 users are considered as imposters).
anyone can help me with that please?
really appreciate any help