I am new to SVM .when i try to learn RAID 1 , first they are creating two RAID 0 strips through
In the next step
next step is
Please guide me what is the mirror and sub mirror. i knew the RAID 1 concept but i like to know the difference between mirror and the sub mirror and one way mirroring , two way mirroring.
Thanks
MaroV
Last edited by vr_mari; 08-15-2009 at 01:38 PM..
Reason: more clarified question
Hi there,
I'm not sure if this is possible, but here is what I'd like to do..
I have an existing 160GB drive in my Redhat 9.0 server that I would like to add an additional 160GB drive to and create a mirrored RAID of the first disk to the new disk. I would like to do this without having to... (2 Replies)
i am working in sun solaris unix platform with storage device T3+
i got an error message mirror failed
i have telneted to the storage and gave the command format
it gives disk not available ,
i have shifted my storage from node A to node B then i gave the same command format by telneting to... (0 Replies)
I've looked a little but haven't found a solid answer, assuming there is one.
What's better, hardware mirroring or ZFS mirroring? Common practice for us was to use the raid controllers on the Sun x86 servers. Now we've been using ZFS mirroring since U6. Any performance difference? Any other... (3 Replies)
Hi,
I have an Ubuntu system which I have an faulted mirror.
I trying to replace the disk, but I'm stuck on that it boots and only showing GRUB
GRUB
## ## End Default Options ##
title Ubuntu 8.04.4 LTS, kernel 2.6.24-26-server
root (hd0,0)
kernel ... (0 Replies)
Hello,
I am trying to convert a single-drive Centos 7.2 installation with LVM into a two-disk mdadm mirror with mrrored LVM. I was able to follow the excellent instructions at:
http://www.dgoradia.com/creating-a-raid1-mirrored-on-an-existing-centos-on-lvm/and did create a two-disk mirror... (1 Reply)
Hi All
BAsed on the below I would like to verifu two things
(1) The udnerlying mirroris for '/mnt' na dit onlcy contaisne 1 sub-mirror, with one sliceon is one disk and hence, data loss on the mount point (the mount point, '/mnt' is backed up)
(2) the Procedure for renewal
# df -kh /mnt... (2 Replies)
Discussion started by: stevie_velvet
2 Replies
LEARN ABOUT PHP
svm
SVM(3) 1 SVM(3)The SVM classINTRODUCTION CLASS SYNOPSIS
SVM
SVM
Constants
o const integer$SVM::C_SVC0
o const integer$SVM::NU_SVC1
o const integer$SVM::ONE_CLASS2
o const integer$SVM::EPSILON_SVR3
o const integer$SVM::NU_SVR4
o const integer$SVM::KERNEL_LINEAR0
o const integer$SVM::KERNEL_POLY1
o const integer$SVM::KERNEL_RBF2
o const integer$SVM::KERNEL_SIGMOID3
o const integer$SVM::KERNEL_PRECOMPUTED4
o const integer$SVM::OPT_TYPE101
o const integer$SVM::OPT_KERNEL_TYPE102
o const integer$SVM::OPT_DEGREE103
o const integer$SVM::OPT_SHRINKING104
o const integer$SVM::OPT_PROPABILITY105
o const integer$SVM::OPT_GAMMA201
o const integer$SVM::OPT_NU202
o const integer$SVM::OPT_EPS203
o const integer$SVM::OPT_P204
o const integer$SVM::OPT_COEF_ZERO205
o const integer$SVM::OPT_C206
o const integer$SVM::OPT_CACHE_SIZE207
Methods
o public SVM::__construct (void )
o public float svm::crossvalidate (array $problem, int $number_of_folds)
o public array SVM::getOptions (void )
o public bool SVM::setOptions (array $params)
o public SVMModel svm::train (array $problem, [array $weights])
PREDEFINED CONSTANTS SVM CONSTANTS
o SVM::C_SVC -The basic C_SVC SVM type. The default, and a good starting point
o SVM::NU_SVC -The NU_SVC type uses a different, more flexible, error weighting
o SVM::ONE_CLASS -One class SVM type. Train just on a single class, using outliers as negative examples
o SVM::EPSILON_SVR -A SVM type for regression (predicting a value rather than just a class)
o SVM::NU_SVR -A NU style SVM regression type
o SVM::KERNEL_LINEAR -A very simple kernel, can work well on large document classification problems
o SVM::KERNEL_POLY -A polynomial kernel
o SVM::KERNEL_RBF -The common Gaussian RBD kernel. Handles non-linear problems well and is a good default for classification
o SVM::KERNEL_SIGMOID -A kernel based on the sigmoid function. Using this makes the SVM very similar to a two layer sigmoid based
neural network
o SVM::KERNEL_PRECOMPUTED -A precomputed kernel - currently unsupported.
o SVM::OPT_TYPE -The options key for the SVM type
o SVM::OPT_KERNEL_TYPE -The options key for the kernel type
o SVM::OPT_DEGREE -
o SVM::OPT_SHRINKING -Training parameter, boolean, for whether to use the shrinking heuristics
o SVM::OPT_PROBABILITY -Training parameter, boolean, for whether to collect and use probability estimates
o SVM::OPT_GAMMA -Algorithm parameter for Poly, RBF and Sigmoid kernel types.
o SVM::OPT_NU -The option key for the nu parameter, only used in the NU_ SVM types
o SVM::OPT_EPS -The option key for the Epsilon parameter, used in epsilon regression
o SVM::OPT_P -Training parameter used by Episilon SVR regression
o SVM::OPT_COEF_ZERO -Algorithm parameter for poly and sigmoid kernels
o SVM::OPT_C -The option for the cost parameter that controls tradeoff between errors and generality - effectively the penalty for
misclassifying training examples.
o SVM::OPT_CACHE_SIZE -Memory cache size, in MB
PHP Documentation Group SVM(3)