[mlpack-svn] r15452 - mlpack/conf/jenkins-conf/benchmark
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Thu Jul 11 10:56:08 EDT 2013
Author: marcus
Date: Thu Jul 11 10:56:08 2013
New Revision: 15452
Log:
Add config with some small datasets to test the benchmark.
Added:
mlpack/conf/jenkins-conf/benchmark/small_config.yaml
Added: mlpack/conf/jenkins-conf/benchmark/small_config.yaml
==============================================================================
--- (empty file)
+++ mlpack/conf/jenkins-conf/benchmark/small_config.yaml Thu Jul 11 10:56:08 2013
@@ -0,0 +1,363 @@
+# MLPACK:
+# A Scalable C++ Machine Learning Library
+library: mlpack
+methods:
+ PCA:
+ run: true
+ script: methods/mlpack/pca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
+ NMF:
+ run: true
+ script: methods/mlpack/nmf.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv']
+ options: '-r 6 -s 42 -u multdist'
+ KMEANS:
+ run: true
+ script: methods/mlpack/kmeans.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ options: '-c 3'
+ NBC:
+ run: true
+ script: methods/mlpack/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
+ 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
+ script: methods/mlpack/lars.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
+
+ LSH:
+ run: false
+ script: methods/mlpack/lsh.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3 -s 42'
+
+ ALLKNN:
+ run: true
+ script: methods/mlpack/allknn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3 -s 42'
+
+ ALLKFN:
+ run: false
+ script: methods/mlpack/allkfn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3'
+
+ ALLKRANN:
+ run: false
+ script: methods/mlpack/allkrann.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3 -t 10'
+
+ RANGESEARCH:
+ run: true
+ script: methods/mlpack/range_search.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/ionosphere.csv']
+ options: '-m 0 -M 20.3'
+
+ GMM:
+ run: false
+ script: methods/mlpack/gmm.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/artificial_2DSignal.csv', 'datasets/artificial_5DSignal.csv', 'datasets/iris.csv']
+ options: '-s 42'
+ DET:
+ run: false
+ script: methods/mlpack/det.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/iris.csv', 'datasets/cloud.csv']
+
+ EMST:
+ run: false
+ script: methods/mlpack/emst.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/iris.csv']
+
+ LinearRegression:
+ run: false
+ 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']]
+
+ LocalCoordinateCoding:
+ run: false
+ script: methods/mlpack/local_coordinate_coding.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 12 -s 42'
+
+ SparseCoding:
+ run: false
+ script: methods/mlpack/sparse_coding.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 12 -s 42 -n 100'
+
+ FastMKS:
+ run: false
+ script: methods/mlpack/fastmks.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 1 -K linear'
+
+ NCA:
+ run: false
+ 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
+ script: methods/mlpack/hmm_train.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/artificial_2DSignal.csv']
+ options: '-t gaussian -n 20 -s 42'
+
+ - files: ['datasets/artificial_1DSignal.csv']
+ options: '-t discrete -n 20 -s 42'
+
+ HMMGENERATE:
+ run: false
+ script: methods/mlpack/hmm_generate.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/artificial_2DSignal_hmm.xml', 'datasets/artificial_1DSignal_hmm.xml']
+ options: '-l 10000'
+
+ HMMLOGLIK:
+ run: false
+ 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'] ]
+
+ HMMVITERBI:
+ run: false
+ 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'] ]
+---
+# MATLAB:
+# Numerical computing environment and programming language.
+library: matlab
+methods:
+ PCA:
+ run: false
+ script: methods/matlab/pca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
+ NMF:
+ run: false
+ script: methods/matlab/nmf.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv']
+ options: '-r 6 -s 42 -u multdist'
+ KMeans:
+ run: false
+ script: methods/matlab/kmeans.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ options: '-c 3'
+
+ NBC:
+ run: false
+ script: methods/mlpack/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: false
+ script: methods/mlpack/allknn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3 -s 42'
+
+ RANGESEARCH:
+ run: false
+ script: methods/mlpack/range_search.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/ionosphere.csv']
+ options: '-M 20.3'
+---
+# Scikit-Learn: machine learning in Python
+library: scikit
+methods:
+ PCA:
+ run: true
+ script: methods/scikit/pca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
+
+ NMF:
+ run: true
+ script: methods/scikit/nmf.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/piano_magnitude_spectogram.csv', 'datasets/wine.csv']
+ options: '-r 6 -u alspgrad'
+
+ KMEANS:
+ run: true
+ script: methods/scikit/kmeans.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ options: '-c 3'
+
+ NBC:
+ run: true
+ 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
+ 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
+ script: methods/scikit/lars.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
+
+ ALLKNN:
+ run: true
+ script: methods/scikit/allknn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3 -s 42'
+---
+# mlpy is a Python module for Machine Learning built on top of NumPy/SciPy
+# and the GNU Scientific Libraries.
+library: mlpy
+methods:
+ PCA:
+ run: true
+ script: methods/mlpy/pca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
+
+ KMEANS:
+ run: true
+ script: methods/mlpy/kmeans.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/iris.csv']
+ options: '-c 3'
+
+ KPCA:
+ run: true
+ 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
+ script: methods/mlpy/lars.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
+
+ ALLKNN:
+ run: true
+ script: methods/mlpy/allknn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3 -s 42'
+---
+# Shogun - A Large Scale Machine Learning Toolbox
+library: shogun
+methods:
+ PCA:
+ run: true
+ script: methods/shogun/pca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cities.csv', 'datasets/faces.csv', 'datasets/iris.csv' , 'datasets/wine.csv']
+
+ KPCA:
+ run: true
+ 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
+ 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
+ script: methods/shogun/allknn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv']
+ options: '-k 3 -s 42'
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