[mlpack-svn] r15513 - mlpack/conf/jenkins-conf/benchmark
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Fri Jul 19 15:13:52 EDT 2013
Author: marcus
Date: Fri Jul 19 15:13:52 2013
New Revision: 15513
Log:
Update small config file to test all current available benchmark scripts.
Modified:
mlpack/conf/jenkins-conf/benchmark/small_config.yaml
Modified: mlpack/conf/jenkins-conf/benchmark/small_config.yaml
==============================================================================
--- mlpack/conf/jenkins-conf/benchmark/small_config.yaml (original)
+++ mlpack/conf/jenkins-conf/benchmark/small_config.yaml Fri Jul 19 15:13:52 2013
@@ -3,27 +3,32 @@
library: mlpack
methods:
PCA:
- run: true
+ run: false
+ iteration: 3
script: methods/mlpack/pca.py
format: [csv, txt]
datasets:
- - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' ,
+ 'datasets/wine.csv', 'datasets/ionosphere.csv', 'datasets/diabetes_X.csv']
NMF:
run: true
+ iteration: 3
script: methods/mlpack/nmf.py
format: [csv, txt]
datasets:
- - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv']
+ - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv', 'datasets/pendigits.csv']
options: '-r 6 -s 42 -u multdist'
KMEANS:
run: true
+ iteration: 3
script: methods/mlpack/kmeans.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ - files: ['datasets/wine.csv', 'datasets/iris.csv', 'datasets/cloud.csv', 'datasets/USCensus1990.csv']
options: '-c 3'
NBC:
run: true
+ iteration: 3
script: methods/mlpack/nbc.py
format: [csv, txt]
datasets:
@@ -31,122 +36,133 @@
['datasets/transfusion_train.csv', 'datasets/transfusion_test.csv'] ]
KPCA:
run: true
+ iteration: 3
script: methods/mlpack/kernel_pca.py
format: [csv, txt]
datasets:
- files: ['datasets/circle_data.csv', 'datasets/arcene_X.csv']
options: '-k polynomial'
-
LARS:
run: true
+ iteration: 3
script: methods/mlpack/lars.py
format: [csv, txt]
datasets:
- - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
-
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'],
+ ['datasets/arcene_X.csv', 'datasets/arcene_y.csv'] ]
LSH:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/lsh.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv']
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv']
options: '-k 3 -s 42'
ALLKNN:
run: true
+ iteration: 3
script: methods/mlpack/allknn.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv']
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv', 'datasets/pendigits.csv']
options: '-k 3 -s 42'
-
ALLKFN:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/allkfn.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv']
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv', 'datasets/pendigits.csv']
options: '-k 3'
-
ALLKRANN:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/allkrann.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv']
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv', 'datasets/pendigits.csv']
options: '-k 3 -t 10'
-
RANGESEARCH:
run: true
+ iteration: 3
script: methods/mlpack/range_search.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv', 'datasets/ionosphere.csv']
+ - files: ['datasets/wine.csv', 'datasets/ionosphere.csv',
+ 'datasets/arcene_X.csv', 'datasets/madelon_X.csv']
options: '-M 20.3'
-
GMM:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/gmm.py
format: [csv, txt]
datasets:
- - files: ['datasets/artificial_2DSignal.csv', 'datasets/artificial_5DSignal.csv', 'datasets/iris.csv']
+ - files: ['datasets/artificial_2DSignal.csv', 'datasets/artificial_5DSignal.csv',
+ 'datasets/iris.csv', 'datasets/vehicle.csv', 'datasets/wine.csv',
+ 'datasets/USCensus1990.csv']
options: '-s 42'
DET:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/det.py
format: [csv, txt]
datasets:
- files: ['datasets/iris.csv', 'datasets/cloud.csv']
-
EMST:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/emst.py
format: [csv, txt]
datasets:
- files: ['datasets/iris.csv']
-
LinearRegression:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/linear_regression.py
format: [csv, txt]
datasets:
- files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
- ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv']]
-
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'],
+ ['datasets/arcene_X.csv', 'datasets/arcene_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
LocalCoordinateCoding:
run: false
+ iteration: 3
script: methods/mlpack/local_coordinate_coding.py
format: [csv, txt]
datasets:
- files: ['datasets/wine.csv']
options: '-k 12 -s 42'
-
SparseCoding:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/sparse_coding.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv']
+ - files: ['datasets/wine.csv', 'datasets/pendigits.csv']
options: '-k 12 -s 42 -n 100'
-
FastMKS:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/fastmks.py
format: [csv, txt]
datasets:
- files: ['datasets/wine.csv']
options: '-k 1 -K linear'
-
NCA:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/nca.py
format: [csv, txt]
datasets:
- files: ['datasets/iris_train.csv', ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
options: '-n 2000 -O sgd -s 42'
-
HMMTRAIN:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/hmm_train.py
format: [csv, txt]
datasets:
@@ -155,30 +171,28 @@
- files: ['datasets/artificial_1DSignal.csv']
options: '-t discrete -n 20 -s 42'
-
HMMGENERATE:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/hmm_generate.py
format: [csv, txt]
datasets:
- - files: ['datasets/artificial_2DSignal_hmm.xml', 'datasets/artificial_1DSignal_hmm.xml']
+ - files: ['datasets/artificial_2DSignal_hmm.xml']
options: '-l 10000'
-
HMMLOGLIK:
- run: false
+ run: true
+ iteration: 3
script: methods/mlpack/hmm_loglik.py
format: [csv, txt]
datasets:
- - files: [ ['datasets/artificial_2DSignal.csv', 'datasets/artificial_2DSignal_hmm.xml'],
- ['datasets/artificial_1DSignal.csv', 'datasets/artificial_1DSignal_hmm.xml'] ]
-
+ - files: [ ['datasets/artificial_2DSignal.csv', 'datasets/artificial_2DSignal_hmm.xml'] ]
HMMVITERBI:
run: false
+ iteration: 3
script: methods/mlpack/hmm_viterbi.py
format: [csv, txt]
datasets:
- - files: [ ['datasets/artificial_2DSignal.csv', 'datasets/artificial_2DSignal_hmm.xml'],
- ['datasets/artificial_1DSignal.csv', 'datasets/artificial_1DSignal_hmm.xml'] ]
+ - files: [ ['datasets/artificial_2DSignal.csv', 'datasets/artificial_2DSignal_hmm.xml'] ]
---
# MATLAB:
# Numerical computing environment and programming language.
@@ -186,105 +200,169 @@
methods:
PCA:
run: true
+ iteration: 3
script: methods/matlab/pca.py
format: [csv, txt]
datasets:
- - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' ,
+ 'datasets/wine.csv', 'datasets/ionosphere.csv', 'datasets/diabetes_X.csv']
NMF:
run: true
+ iteration: 3
script: methods/matlab/nmf.py
format: [csv, txt]
datasets:
- - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv']
+ - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv', 'datasets/pendigits.csv']
options: '-r 6 -s 42 -u multdist'
KMEANS:
run: true
+ iteration: 3
script: methods/matlab/kmeans.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ - files: ['datasets/wine.csv', 'datasets/iris.csv', 'datasets/cloud.csv', 'datasets/USCensus1990.csv']
options: '-c 3'
-
NBC:
run: true
- script: methods/mlpack/nbc.py
+ iteration: 3
+ script: methods/matlab/nbc.py
format: [csv, txt]
datasets:
- files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv'],
['datasets/transfusion_train.csv', 'datasets/transfusion_test.csv'] ]
-
ALLKNN:
run: true
- script: methods/mlpack/allknn.py
+ iteration: 3
+ script: methods/matlab/allknn.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv']
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv', 'datasets/pendigits.csv']
options: '-k 3 -s 42'
-
RANGESEARCH:
run: true
- script: methods/mlpack/range_search.py
+ iteration: 3
+ script: methods/matlab/range_search.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv', 'datasets/ionosphere.csv']
+ - files: ['datasets/wine.csv', 'datasets/ionosphere.csv',
+ 'datasets/arcene_X.csv', 'datasets/madelon_X.csv']
options: '-M 20.3'
+ LinearRegression:
+ run: true
+ iteration: 3
+ script: methods/matlab/linear_regression.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'],
+ ['datasets/arcene_X.csv', 'datasets/arcene_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
+ HMMGENERATE:
+ run: true
+ iteration: 3
+ script: methods/matlab/hmm_generate.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/artificial_2DSignal_hmm.xml']
+ options: '-l 10000'
+ HMMVITERBI:
+ run: false
+ iteration: 3
+ script: methods/matlab/hmm_viterbi.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/artificial_2DSignal.csv', 'datasets/artificial_2DSignal_hmm.xml'] ]
---
# Scikit-Learn: machine learning in Python
library: scikit
methods:
PCA:
run: true
+ iteration: 3
script: methods/scikit/pca.py
format: [csv, txt]
datasets:
- - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
-
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' ,
+ 'datasets/wine.csv', 'datasets/ionosphere.csv', 'datasets/diabetes_X.csv']
NMF:
run: true
+ iteration: 3
script: methods/scikit/nmf.py
format: [csv, txt]
datasets:
- - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv']
+ - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv', 'datasets/pendigits.csv']
options: '-r 6 -u alspgrad'
-
KMEANS:
run: true
+ iteration: 3
script: methods/scikit/kmeans.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ - files: ['datasets/wine.csv', 'datasets/iris.csv', 'datasets/cloud.csv', 'datasets/USCensus1990.csv']
options: '-c 3'
-
NBC:
run: true
+ iteration: 3
script: methods/scikit/nbc.py
format: [csv, txt]
datasets:
- files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv'],
['datasets/transfusion_train.csv', 'datasets/transfusion_test.csv'] ]
-
KPCA:
run: true
+ iteration: 3
script: methods/scikit/kernel_pca.py
format: [csv, txt]
datasets:
- files: ['datasets/circle_data.csv', 'datasets/arcene_X.csv']
options: '-k polynomial'
-
LARS:
run: true
+ iteration: 3
script: methods/scikit/lars.py
format: [csv, txt]
datasets:
- - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
-
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
ALLKNN:
run: true
+ iteration: 3
script: methods/scikit/allknn.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv']
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv', 'datasets/pendigits.csv']
options: '-k 3 -s 42'
+ GMM:
+ run: true
+ iteration: 3
+ script: methods/scikit/gmm.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/artificial_2DSignal.csv', 'datasets/artificial_5DSignal.csv',
+ 'datasets/iris.csv', 'datasets/vehicle.csv', 'datasets/wine.csv',
+ 'datasets/USCensus1990.csv']
+ options: '-s 42'
+
+ LinearRegression:
+ run: true
+ iteration: 3
+ script: methods/scikit/linear_regression.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'],
+ ['datasets/arcene_X.csv', 'datasets/arcene_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
+ SparseCoding:
+ run: true
+ iteration: 3
+ script: methods/scikit/sparse_coding.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/pendigits.csv']
+ options: '-k 12 -s 42 -n 100'
---
# mlpy is a Python module for Machine Learning built on top of NumPy/SciPy
# and the GNU Scientific Libraries.
@@ -292,105 +370,162 @@
methods:
PCA:
run: true
+ iteration: 3
script: methods/mlpy/pca.py
format: [csv, txt]
datasets:
- - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
-
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' ,
+ 'datasets/wine.csv', 'datasets/ionosphere.csv', 'datasets/diabetes_X.csv']
KMEANS:
run: true
+ iteration: 3
script: methods/mlpy/kmeans.py
format: [csv, txt]
datasets:
- - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ - files: ['datasets/wine.csv', 'datasets/iris.csv', 'datasets/cloud.csv', 'datasets/USCensus1990.csv']
options: '-c 3'
-
KPCA:
run: true
+ iteration: 3
script: methods/mlpy/kernel_pca.py
format: [csv, txt]
datasets:
- files: ['datasets/circle_data.csv', 'datasets/arcene_X.csv']
options: '-k polynomial'
-
LARS:
run: true
+ iteration: 3
script: methods/mlpy/lars.py
format: [csv, txt]
datasets:
- - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
-
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
ALLKNN:
run: true
+ iteration: 3
script: methods/mlpy/allknn.py
format: [csv, txt]
datasets:
- files: ['datasets/wine.csv']
options: '-k 3 -s 42'
+ LinearRegression:
+ run: true
+ iteration: 3
+ script: methods/mlpy/linear_regression.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'],
+ ['datasets/arcene_X.csv', 'datasets/arcene_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
---
# Shogun - A Large Scale Machine Learning Toolbox
library: shogun
methods:
PCA:
run: true
+ iteration: 3
script: methods/shogun/pca.py
format: [csv, txt]
datasets:
- - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
-
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' ,
+ 'datasets/wine.csv', 'datasets/ionosphere.csv', 'datasets/diabetes_X.csv']
+ KMEANS:
+ run: true
+ iteration: 3
+ script: methods/shogun/kmeans.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/iris.csv', 'datasets/cloud.csv', 'datasets/USCensus1990.csv']
+ options: '-c 3'
KPCA:
run: true
+ iteration: 3
script: methods/shogun/kernel_pca.py
format: [csv, txt]
datasets:
- files: ['datasets/circle_data.csv', 'datasets/arcene_X.csv']
options: '-k polynomial'
-
NBC:
run: true
+ iteration: 3
script: methods/shogun/nbc.py
format: [csv, txt]
datasets:
- files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv'],
['datasets/transfusion_train.csv', 'datasets/transfusion_test.csv'] ]
-
ALLKNN:
run: true
+ iteration: 3
script: methods/shogun/allknn.py
format: [csv, txt]
datasets:
- files: ['datasets/wine.csv']
options: '-k 3 -s 42'
+ GMM:
+ run: true
+ iteration: 3
+ script: methods/shogun/gmm.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/artificial_2DSignal.csv', 'datasets/artificial_5DSignal.csv',
+ 'datasets/iris.csv', 'datasets/vehicle.csv', 'datasets/wine.csv']
+ options: '-s 42'
+ LinearRegression:
+ run: true
+ iteration: 3
+ script: methods/shogun/linear_regression.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'],
+ ['datasets/arcene_X.csv', 'datasets/arcene_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
---
# Weka: Data Mining Software in Java
library: weka
methods:
PCA:
run: true
+ iteration: 3
script: methods/weka/pca.py
- format: [csv, txt]
+ format: [arff]
datasets:
- - files: ['datasets/iris.arff']
-
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' ,
+ 'datasets/wine.csv', 'datasets/ionosphere.csv', 'datasets/diabetes_X.csv']
NBC:
run: true
+ iteration: 3
script: methods/weka/nbc.py
- format: [csv, txt]
+ format: [arff]
datasets:
- - files: [ ['datasets/iris_train.arff', 'datasets/iris_test.arff'] ]
-
+ - files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv'],
+ ['datasets/transfusion_train.csv', 'datasets/transfusion_test.csv'] ]
KMEANS:
run: true
+ iteration: 3
script: methods/weka/kmeans.py
- format: [csv, txt]
+ format: [arff]
datasets:
- - files: ['datasets/iris.arff']
+ - files: ['datasets/wine.csv', 'datasets/iris.csv', 'datasets/cloud.csv', 'datasets/USCensus1990.csv']
options: '-c 3'
-
ALLKNN:
run: true
+ iteration: 3
script: methods/weka/allknn.py
- format: [csv, txt]
+ format: [arff]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv']
+ options: '-k 3 -s 42'
+ LinearRegression:
+ run: true
+ iteration: 3
+ script: methods/weka/linear_regression.py
+ format: [arff]
datasets:
- - files: ['datasets/wine.arff']
- options: '-k 3 -s 42'
\ No newline at end of file
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'],
+ ['datasets/cosExp_X.csv', 'datasets/cosExp_y.csv'] ]
\ No newline at end of file
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