---
name: "svm-landscape"
section: "1"
platform: "linux"
package: "python-mlpy"
version: "2.2.0~dfsg1-2.1"
release: "Debian 8 (Jessie)"
platforms: ["linux"]
url: "https://new.carta.tech/svm-landscape"
---

# svm-landscape(1)

Command line interface to svm-landscape in mlpy (version 2.2.0)

## NAME

svm-landscape - Command line interface to svm-landscape in mlpy (version 2.2.0)

## SYNOPSIS

**svm-landscape** \[*options*\]

## OPTIONS

- **-h**, **--help**

  show this help message and exit

- **-d** FILE, **--data**=*FILE*

  data - required

- **-s**, **--standardize**

  standardize data

- **-n**, **--normalize**

  normalize data

- **-k** K

  k for k-fold cross validation

- **-c** SETS PAIRS

  sets and pairs for monte carlo cross validation

- **-S**, **--stratified**

  for stratified cv

- **-K** KERNEL, **--kernel**=*KERNEL*

  kernel: 'linear', 'gaussian', 'polynomial', 'tr' \[default linear\]

- **-P** KPARAMETER, **--kparameter**=*KPARAMETER*

  kernel parameter (two sigma squared) for gaussian and polynomial kernels \[default 0.1\]

- **-o** COST, **--cost**=*COST*

  for cost-sensitive classification \[-1.0, 1.0\] \[default 0.0\]

- **-m** MIN, **--min**=*MIN*

  min value for regularization parameter \[default **-5\]**

- **-M** MAX, **--max**=*MAX*

  max value for regularization parameter \[default 5\]

- **-p** STEPS, **--steps**=*STEPS*

  steps for regularization parameter \[default 11\]

- **-e** SCALE, **--scale**=*SCALE*

  scale for regularization parameter: 'lin' or 'log' \[default log\]

- **-l**, **--lists**

  Canberra distance indicator

- **-a**, **--auc**

  Wmw\_auc metric computation