bob
2.6.2
Installation Instructions
Getting started with Bob
Bob’s Core Routines
Bob’s Math Routines
Bob’s Metric Routines
Bob’s Core I/O Routines
Bob’s I/O Routines for Images of Various type
Bob’s Video I/O Routines
Bob’s Audio I/O Routines
Matlab(R) I/O Support for Bob
Bob’s Signal Processing Routines
Bob’s Audio Processing Routines
Bob’s Basic Image Processing Routines
Bob’s Color Conversion Routines
Bob’s Drawing Routines
Bob’s Gabor wavelet routines
Bob’s Face Detection Routines
Python Bindings to Liu’s Optical Flow Framework
Python Bindings to Horn & Schunck’s Optical Flow Framework
Python Bindings to the Flandmark Keypoint Localizer for Frontal Faces
Bob Activation Functors
Bob Linear Machines and Trainers
Bob’s Multi-Layer Perceptron Machines
Documentation
Multi-Layer Perceptron (MLP) Machines and Trainers
Python API
C++ API
Indices and tables
Bob-LIBSVM Python Bindings
Expectation Maximization Machine Learning Tools
Generalized Boosting Framework using Stump and Look Up Table (LUT) based Weak Classifiers
Bob Database Support
MNIST Database Interface
Wine Database
AT&T Database of Faces Verification Protocol
Iris Flower Data Set
Bob Python/C++ Extensions
Blitz++/Python Arrays
bob
Docs
»
Bob’s Multi-Layer Perceptron Machines
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Bob’s Multi-Layer Perceptron Machines
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This module contains base functionality for training and using Multi-Layer Perceptrons in Bob.
Documentation
¶
Multi-Layer Perceptron (MLP) Machines and Trainers
Python API
C++ API
Machine
Cost
Data Shuffler
Trainers
Pure C/C++ API
Indices and tables
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Index
Module Index
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