GitHub - pshizhsysu/dwarmstart: A distributed algorithm for parameter selection of logistic regression using warm start

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A distributed algorithm for parameter selection of logistic regression using warm start

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Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
blas		blas
Makefile		Makefile
README		README
classifier.cpp		classifier.cpp
classifier.h		classifier.h
linear.cpp		linear.cpp
linear.def		linear.def
linear.h		linear.h
linear_backup.cpp		linear_backup.cpp
machinefile		machinefile
mpi_fun.h		mpi_fun.h
predict.c		predict.c
running.sh		running.sh
split.py		split.py
structures.h		structures.h
train.c		train.c
tron.cpp		tron.cpp
tron.h		tron.h
version_for_dwarmstart		version_for_dwarmstart

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Install
=======
in unix, run 'make' command to obtain 'train'

`train' Usage
=============

"Usage: train [options] training_set_file [model_file]\n"
	"options:\n"
	"-c cost : set the parameter C (default 1)\n"
	"-e epsilon : set termination criterion for TRON, default 0.01\n"
	"-g epsilon_cg : set termination criterion for CG, default 0.1\n"
	"-v k: k-fold cross validation\n"
	"-C : find the best C\n"

Examples
========

> train data_file

Train a logistic regression model.

> train -v 5 -e 0.001 data_file

Do five-fold cross-validation using LR.
Use a smaller stopping tolerance 0.001 than the default
0.1 if you want more accurate solutions.