When I run Weka and I see all classifiers, I don't see neural networks classifiers. Why?
I found it in Functions->MultilayerPerception
From the command line:
java -cp '.:/usr/share/weka/lib/weka.jar' \
weka.classifiers.functions.MultilayerPerceptron -t yourfile.arff
Related
I'm stuck up using RSim target options.
I've created an .exe from a Simulink model "my_model" using RSim target.
Now my aim is to run this .exe and control the solver options using a .mat file.
I am trying to run the following command on CMD:
my_model.exe -i input.mat -tf 10 -o output.mat -S solver_options.mat
But the output.mat file of the model does not correspond to the sampling time I've provided in sover_options.mat.
I am following the inputs arguments provided by RSim, as shown below:
It seems that RSim is not reading new solver_options parameters.
My solver_options.mat file is provided below:
Could anyone help me, please?
I have been running Minizinc models from the command line, and I get final solutions as output.
I know I can make Minizic print intermedite solutions in the IDE. How can I make the same from the command line, so that they are printed as output like in the IDE? Btw, I'm refering to the output Minizinc prints by default, not to the 'output' (the one that acts like print) that you can include in the code of the model.
To output intermediate solutions you can use the -a flag on optimisation problems. So for example minizinc --solver gecode -a model.mzn data.dzn will solve model.mzn with data.dzn on the Gecode solver and output all intermediate solutions.
Note, however, that the -a flag has has a few peculiarities:
-a for satisfiability will output all solutions instead of intermediate solutions. So while scripting you need to be careful.
Not all solvers support the -a flag. Not all solver will have (or output) intermediate solution.
I am trying to use the autotune-validation command to check the f1 score of a dataset I am working in.
I tested fastText in two different machines (Ubuntu and MAC), but I got the following error:
Unknown argument: -autotune-validation
The following arguments are mandatory:
-input training file path
-output output file path
The following arguments are optional:
-verbose verbosity level [2]
...
I tried to read the documentation, but according to the fastText website, this command should work fine.
./fasttext supervised -input commits.train -output commits -autotune-validation commits.valid
I expected the -autotune-validation command to work fine as described here
I have created several separate experiments in BehaviorSpace and would like to run all the experiments in one execution. I read a potential solution here that makes use of an experiment-number global variable to set variables according to a parameter set, and then use BehaviorSpace to run each "experiment-number". However, this method would require me to set over 100 individual experiments. Instead, I would like just a few experiments, but each experiment varies parameter values. I would like to somehow perform all experiments automatically in one execution instead of picking each experiment separately from the BehaviorSpace GUI. Does anybody have suggestions on how multiple experiments can be ran automatically? I have read the documentation for headless mode, but it seems this still only offers a method to run a single experiment from the command line. I would ideally accomplish this in headless mode, and be able to put results of each experiment in different files. Your ideas are much appreciated.
java -Xmx1024m -Dfile.encoding=UTF-8 -cp NetLogo.jar \
org.nlogo.headless.Main \
--model MYMODEL.nlogo \
--experiment experiment1 \
--experiment experiment2 \
--experiment experiment3 \
--experiment experiment4 \
--experiment experiment5 \
--table -
I want to redirect Caffe's output from the terminal to a file (say output.txt). I'm using the command
caffe train -solver=expt/solver.prototxt > output.txt`
However, the > operator doesn't seem to be working and Caffe spits out all the output on to the terminal. I'm using Ubuntu 14.04.
Can't seem to figure out why > is not working with Caffe. Any help is much appreciated. Thank you.
You need to redierect stderr as well
caffe train ... > output.txt 2>&1
The redirection operator > redirects only stdout, caffe is using sterr as well. You might want to set GLOG_logtosterr=1 as well.