Does anyone know the maximum dimension that svm can deal with in R?
I am working on support vector regression.
My data set is 1721*41030
1721 samples
41030 predictors
Some information about my machine:
cat /proc/cpuinfo
processor : 0
vendor_id : GenuineIntel
cpu family : 15
model : 4
model name : Intel(R) Xeon(TM) CPU 2.80GHz
stepping : 10
cpu MHz : 2793.264
cache size : 2048 KB
fpu : yes
fpu_exception : yes
cpuid level : 3
wp : yes
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr
pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm
syscall lm pni monitor ds_cpl cid cx16 xtpr ts
bogomips : 5537.79
clflush size : 64
cache_alignment : 128
address sizes : 36 bits physical, 48 bits virtual
power management:
[aiminy at omega ~]$ cat /proc/meminfo
MemTotal: 2058192 kB
MemFree: 311068 kB
Buffers: 924 kB
Cached: 15216 kB
SwapCached: 176776 kB
Active: 1543584 kB
Inactive: 153280 kB
HighTotal: 0 kB
HighFree: 0 kB
LowTotal: 2058192 kB
LowFree: 311068 kB
SwapTotal: 2048184 kB
SwapFree: 130480 kB
Dirty: 0 kB
Writeback: 0 kB
Mapped: 1651224 kB
Slab: 18476 kB
Committed_AS: 3654596 kB
PageTables: 14044 kB
VmallocTotal: 536870911 kB
VmallocUsed: 297744 kB
VmallocChunk: 536572807 kB
HugePages_Total: 0
HugePages_Free: 0
Hugepagesize: 2048 kB
Thanks,
AMY
