RTModel

Trains a model for the retention time prediction of peptides from a training set.

Web Documentation for RTModel

Options

version
Version of the tool that generated this parameters file.
svm_type
the type of the svm (NU_SVR or EPSILON_SVR for RT prediction, automatically set to C_SVC for separation prediction)
nu
the nu parameter [0..1] of the svm (for nu-SVR)
p
the epsilon parameter of the svm (for epsilon-SVR)
c
the penalty parameter of the svm
kernel_type
the kernel type of the svm
degree
the degree parameter of the kernel function of the svm (POLY kernel)
border_length
length of the POBK
max_std
max standard deviation for a peptide to be included (if there are several ones for one peptide string)(median is taken)
k_mer_length
k_mer length of the POBK
sigma
sigma of the POBK
total_gradient_time
the time (in seconds) of the gradient (only for RT prediction)
first_dim_rt
if set the model will be built for first_dim_rt
additive_cv
if the step sizes should be interpreted additively (otherwise the actual value is multiplied with the step size to get the new value
log
Name of log file (created only when specified)
debug
Sets the debug level
threads
Sets the number of threads allowed to be used by the TOPP tool
no_progress
Disables progress logging to command line
force
Overrides tool-specific checks
test
Enables the test mode (needed for internal use only)
skip_cv
Set to enable Cross-Validation or set to true if the model should just be trained with 1 set of specified parameters.
number_of_runs
number of runs for the CV (each run creates a new random partition of the data)
number_of_partitions
number of CV partitions
degree_start
starting point of degree
degree_step_size
step size point of degree
degree_stop
stopping point of degree
p_start
starting point of p
p_step_size
step size point of p
p_stop
stopping point of p
c_start
starting point of c
c_step_size
step size of c
c_stop
stopping point of c
nu_start
starting point of nu
nu_step_size
step size of nu
nu_stop
stopping point of nu
sigma_start
starting point of sigma
sigma_step_size
step size of sigma
sigma_stop
stopping point of sigma

Input Ports

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This is the name of the input file (RT prediction). It is assumed that the file type is idXML. Alternatively you can provide a .txt file having a sequence and the corresponding rt per line.#br# [idXML,txt,opt.]
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input file with positive examples (peptide separation prediction)#br# [idXML,opt.]
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input file with negative examples (peptide separation prediction)#br# [idXML,opt.]

Output Ports

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output file: the model in libsvm format [txt]
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output file with additional model parameters when using the OLIGO kernel [paramXML]
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output file with the used training dataset when using the OLIGO kernel [txt]

Views

RTModel Std Output
The text sent to standard out during the execution of RTModel.
RTModel Error Output
The text sent to standard error during the execution of RTModel. (If it appears in gray, it's the output of a previously failing run which is preserved for your trouble shooting.)

Workflows

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Links

Developers

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