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2.1 Introduction
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PLearn User's Guide How to
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PLearn User's Guide How to
Contents
1
. Tutorial
1
.
1
The plearn Commands and Help
1
.
2
Data Matrices
1
.
3
Viewing Data Matrices
1
.
4
vmat File Formats
1
.
5
PLearn Objects, Their Serialization and Specification
1
.
6
plearn Learner
1
.
7
A density estimation example
1
.
8
A classification example
1
.
9
Running a Full Experiment: PTester
1
.
9
.
1
Process Underlying PTester
1
.
9
.
2
Experiment Directory
1
.
9
.
3
Example
1
.
10
Python Preprocessing
2
. Older Tutorial
2
.
1
Introduction
2
.
2
A basic classification problem
2
.
2
.
1
First steps
2
.
2
.
2
What have we done?
2
.
3
A second example
2
.
3
.
1
What have we done?
2
.
4
Conclusion
3
. Basics
3
.
1
The plearn Program
3
.
2
Essential Commmands
3
.
3
Essential Classes
3
.
4
The .plearn Object File Format
3
.
5
The .amat File Format
3
.
6
The .pmat File Format
3
.
7
The .vmat File Format
4
. Howto
4
.
1
How to Build a Neural Network?
5
. Advanced
5
.
1
The .dmat/ Format
5
.
2
The VPL language
5
.
3
The Metadata Directory
6
. Appendix A: File Formats
6
.
1
The .plearn and .psave Formats
6
.
1
.
1
Generalities on mixing ascii and binary
6
.
1
.
2
TVec and TMat
6
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1
.
3
Binary PLearn format for base types
6
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1
.
4
Ascii PLearn format for a sequence
6
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1
.
5
Binary PLearn format for a sequence
