[mlpack-svn] r17215 - mlpack/conf/jenkins-conf/benchmarks
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Wed Oct 8 12:18:46 EDT 2014
Author: rcurtin
Date: Wed Oct 8 12:18:46 2014
New Revision: 17215
Log:
Add a benchmark for mlpack to be run daily.
Added:
mlpack/conf/jenkins-conf/benchmarks/
mlpack/conf/jenkins-conf/benchmarks/daily-benchmark.yaml
Added: mlpack/conf/jenkins-conf/benchmarks/daily-benchmark.yaml
==============================================================================
--- (empty file)
+++ mlpack/conf/jenkins-conf/benchmarks/daily-benchmark.yaml Wed Oct 8 12:18:46 2014
@@ -0,0 +1,525 @@
+# Block for general settings.
+library: general
+settings:
+ # A short timeout, since we want to run this nightly.
+ timeout: 1000
+ database: 'reports/benchmark.db'
+ # These shouldn't matter with the newer js interface.
+ keepReports: 20
+ bootstrap: 10
+ libraries: ['mlpack'] # Only mlpack in this configuration.
+ version: ['trunk']
+
+---
+library: mlpack
+methods:
+ ALLKNN:
+ run: ['timing']
+ script: methods/mlpack/allknn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --single'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --single --cover_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --cover_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --cover_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --single --r_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --r_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --random_basis --seed 42'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --naive'
+
+ ALLKFN:
+ run: ['timing']
+ script: methods/mlpack/allkfn.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --single'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --single --cover_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --cover_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --cover_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --single --r_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --r_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --naive'
+
+ ALLKRANN:
+ run: ['timing']
+ script: methods/mlpack/allkrann.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --alpha 0.9'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --alpha 0.9 --tau 10'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --sample_at_leaves'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --sample_at_leaves --single'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --first_leaf_exact'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --first_leaf_exact --single'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --cover_tree'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '-k 3 --cover_tree --single'
+
+ DecisionStump:
+ run: ['timing']
+ script: methods/mlpack/decision_stump.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv'],
+ ['datasets/optdigits_train.csv', 'datasets/optdigits_test.csv'] ]
+
+ - files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv'],
+ ['datasets/optdigits_train.csv', 'datasets/optdigits_test.csv'] ]
+ options: '-b 20'
+
+ DET:
+ run: ['timing']
+ script: methods/mlpack/det.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/iris.csv', 'datasets/cloud.csv',
+ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
+
+ - files: ['datasets/iris.csv', 'datasets/cloud.csv',
+ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'] ]
+ options: '-f 0'
+
+ EMST:
+ run: ['timing']
+ script: methods/mlpack/emst.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '--naive'
+
+ - files: ['datasets/cloud.csv', 'datasets/isolet.csv',
+ 'datasets/covtype.csv', 'datasets/corel-histogram.csv']
+ options: '--leaf_size 20'
+
+ FastMKS:
+ run: ['timing']
+ script: methods/mlpack/fastmks.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/optdigits.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '-k 3 --kernel linear'
+
+ - files: ['datasets/optdigits.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '-k 3 --kernel linear --single'
+
+ - files: ['datasets/optdigits.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '-k 3 --kernel gaussian'
+
+ - files: ['datasets/optdigits.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '-k 3 --kernel gaussian --single'
+
+ - files: ['datasets/optdigits.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '-k 3 --kernel polynomial --degree 2'
+
+ - files: ['datasets/optdigits.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '-k 3 --kernel polynomial --degree 2 --single'
+
+ GMM:
+ run: ['timing']
+ iteration: 5
+ script: methods/mlpack/gmm.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/iris.csv', 'datasets/wine.csv']
+ options: '--gaussians 3 --seed 42'
+
+ - files: ['datasets/iris.csv', 'datasets/wine.csv']
+ options: '--gaussians 3 --seed 42 --no_force_positive'
+
+ - files: ['datasets/iris.csv', 'datasets/wine.csv']
+ options: '--gaussians 3 --seed 42 --noise 0.1'
+
+ - files: ['datasets/iris.csv', 'datasets/wine.csv']
+ options: '--gaussians 3 --seed 42 --trials 20'
+
+ - files: ['datasets/iris.csv', 'datasets/wine.csv']
+ options: '--gaussians 3 --seed 42 --trials 20 --refined_start'
+
+ - files: ['datasets/optdigits.csv']
+ options: '--gaussians 10 --seed 42'
+
+ - files: ['datasets/optdigits.csv']
+ options: '--gaussians 10 --seed 42 --no_force_positive'
+
+ - files: ['datasets/optdigits.csv']
+ options: '--gaussians 10 --seed 42 --noise 0.1'
+
+ - files: ['datasets/optdigits.csv']
+ options: '--gaussians 10 --seed 42 --trials 20'
+
+ - files: ['datasets/optdigits.csv']
+ options: '--gaussians 10 --seed 42 --trials 20 --refined_start'
+
+ HMMTRAIN:
+ run: ['timing']
+ script: methods/mlpack/hmm_train.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/artificial_2DSignal.csv']
+ options: '--type gaussian --states 20 --seed 42'
+
+ - files: ['datasets/artificial_1DSignal.csv']
+ options: '--type discrete --states 20 --seed 42'
+
+ HMMGENERATE:
+ run: ['timing']
+ script: methods/mlpack/hmm_generate.py
+ format: [csv, txt, xml]
+ datasets:
+ - files: ['datasets/artificial_2DSignal_hmm.xml', 'datasets/artificial_1DSignal_hmm.xml']
+ options: '--length 10000'
+
+ HMMLOGLIK:
+ run: ['timing']
+ script: methods/mlpack/hmm_loglik.py
+ format: [csv, txt, xml]
+ datasets:
+ - files: [ ['datasets/artificial_2DSignal.csv', 'datasets/artificial_2DSignal_hmm.xml'],
+ ['datasets/artificial_1DSignal.csv', 'datasets/artificial_1DSignal_hmm.xml'] ]
+
+ HMMVITERBI:
+ run: ['timing']
+ script: methods/mlpack/hmm_viterbi.py
+ format: [csv, txt, xml]
+ datasets:
+ - files: [ ['datasets/artificial_2DSignal.csv', 'datasets/artificial_2DSignal_hmm.xml'],
+ ['datasets/artificial_1DSignal.csv', 'datasets/artificial_1DSignal_hmm.xml'] ]
+
+ KPCA:
+ run: ['timing']
+ script: methods/mlpack/kernel_pca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel linear --new_dimensionality 2'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel gaussian --new_dimensionality 2'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel polynomial --degree 2 --new_dimensionality 2'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel hyptan --new_dimensionality 2'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel linear --new_dimensionality 2 --nystroem_method --sampling random'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel gaussian --new_dimensionality 2 --nystroem_method --sampling random'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel polynomial --degree 2 --new_dimensionality 2 --nystroem_method --sampling random'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel hyptan --degree 2 --new_dimensionality 2 --nystroem_method --sampling random'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel linear --new_dimensionality 2 --nystroem_method --sampling kmeans'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel gaussian --new_dimensionality 2 --nystroem_method --sampling kmeans'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel polynomial --degree 2 --new_dimensionality 2 --nystroem_method --sampling kmeans'
+
+ - files: ['datasets/circle_data.csv', 'datasets/abalone.csv']
+ options: '--kernel hyptan --degree 2 --new_dimensionality 2 --nystroem_method --sampling kmeans'
+
+ KMEANS:
+ run: ['timing']
+ script: methods/mlpack/kmeans.py
+ format: [csv, txt, arff]
+ datasets:
+ - files: ['datasets/cloud.csv', 'datasets/cloud_centroids.csv']
+ options: '--clusters 5'
+
+ - files: ['datasets/cloud.csv', 'datasets/cloud_centroids.csv']
+ options: '--clusters 5 --allow_empty_clusters'
+
+ - files: ['datasets/USCensus1990.csv', 'datasets/USCensus1990.csv']
+ options: '--clusters 6'
+
+ - files: ['datasets/USCensus1990.csv', 'datasets/USCensus1990.csv']
+ options: '--clusters 6 --allow_empty_clusters'
+
+ LARS:
+ run: ['timing']
+ script: methods/mlpack/lars.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'] ]
+ options: '--lambda1 0.01'
+
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'] ]
+ options: '--lambda1 0.01 --lambda2 0.005'
+
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'] ]
+ options: '--lambda1 0.01 --use_cholesky'
+
+ - files: [ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ ['datasets/madelon_X.csv', 'datasets/madelon_y.csv'] ]
+ options: '--lambda1 0.01 --lambda2 0.005 --use_cholesky'
+
+ LinearRegression:
+ run: ['timing']
+ script: methods/mlpack/linear_regression.py
+ format: [csv, txt]
+ datasets:
+ - files: [ ['datasets/diabetes_X.csv'], ['datasets/cosExp_X.csv'],
+ ['datasets/madelon_train.csv', 'datasets/madelon_test.csv'] ]
+
+ LocalCoordinateCoding:
+ run: ['timing']
+ script: methods/mlpack/local_coordinate_coding.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/pendigits.csv']
+ options: '--atoms 12 --seed 42'
+
+ - files: ['datasets/pendigits.csv']
+ options: '--atoms 12 --seed 42 --normalize'
+
+ - files: ['datasets/pendigits.csv']
+ options: '--atoms 12 --seed 42 --normalize --lambda 0.1'
+
+ LSH:
+ run: ['timing']
+ script: methods/mlpack/lsh.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv', 'datasets/covtype.csv']
+ options: '-k 3 --seed 42'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv', 'datasets/covtype.csv']
+ options: '-k 3 --seed 42 --bucket_size 50'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv', 'datasets/covtype.csv']
+ options: '-k 3 --seed 42 --tables 40'
+
+ NBC:
+ run: ['timing']
+ 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'],
+ ['datasets/madelon_train.csv', 'datasets/madelon_test.csv'] ]
+
+ - files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv'],
+ ['datasets/transfusion_train.csv', 'datasets/transfusion_test.csv'],
+ ['datasets/madelon_train.csv', 'datasets/madelon_test.csv'] ]
+ options: '--incremental_variance'
+
+ NCA:
+ run: ['timing']
+ script: methods/mlpack/nca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/iris_train.csv',
+ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ 'datasets/wine.csv', 'datasets/optdigits.csv']
+ options: '--optimizer sgd --max_iterations 2000 --seed 42'
+
+ - files: ['datasets/iris_train.csv',
+ ['datasets/diabetes_X.csv', 'datasets/diabetes_y.csv'],
+ 'datasets/wine.csv', 'datasets/optdigits.csv']
+ options: '--optimizer lbfgs --max_iterations 2000 --seed 42'
+
+ NMF:
+ run: ['timing']
+ script: methods/mlpack/nmf.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/ionosphere.csv', 'datasets/piano_magnitude_spectogram.csv',
+ 'datasets/optdigits.csv', 'datasets/isolet.csv']
+ options: '--rank 6 --seed 42 --update_rules multdist'
+
+ - files: ['datasets/ionosphere.csv', 'datasets/piano_magnitude_spectogram.csv',
+ 'datasets/optdigits.csv', 'datasets/isolet.csv']
+ options: '--rank 6 --seed 42 --update_rules multdiv'
+
+ - files: ['datasets/ionosphere.csv', 'datasets/piano_magnitude_spectogram.csv',
+ 'datasets/optdigits.csv', 'datasets/isolet.csv']
+ options: '--rank 6 --seed 42 --update_rules als'
+
+ PCA:
+ run: ['timing']
+ script: methods/mlpack/pca.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/iris.csv', 'datasets/wine.csv',
+ 'datasets/cities.csv', 'datasets/diabetes_X.csv']
+
+ - files: ['datasets/iris.csv', 'datasets/wine.csv',
+ 'datasets/cities.csv', 'datasets/diabetes_X.csv']
+ options: '--new_dimensionality 2'
+
+ - files: ['datasets/iris.csv', 'datasets/wine.csv',
+ 'datasets/cities.csv', 'datasets/diabetes_X.csv']
+ options: '--var_to_retain 0.7 --scale'
+
+ PERCEPTRON:
+ run: ['timing']
+ script: methods/mlpack/perceptron.py
+ format: [csv, txt, arff]
+ datasets:
+ - files: [ ['datasets/iris_train.csv', 'datasets/iris_test.csv', 'datasets/iris_labels.csv'],
+ ['datasets/oilspill_train.csv', 'datasets/oilspill_test.csv', 'datasets/oilspill_labels.csv'],
+ ['datasets/ecoli_train.csv', 'datasets/ecoli_test.csv', 'datasets/ecoli_labels.csv'] ]
+ options: '--iterations 10000'
+
+ RANGESEARCH:
+ run: ['timing']
+ script: methods/mlpack/range_search.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --single'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --single --cover_tree'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --cover_tree'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --naive'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --min 0.01'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --min 0.01 --single'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --min 0.01 --cover_tree'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --min 0.01 --single --cover_tree'
+
+ - files: ['datasets/wine.csv', 'datasets/cloud.csv',
+ 'datasets/corel-histogram.csv']
+ options: '--max 0.02 --min 0.01 --naive'
+
+ SparseCoding:
+ run: ['timing']
+ script: methods/mlpack/sparse_coding.py
+ format: [csv, txt]
+ datasets:
+ - files: ['datasets/pendigits.csv']
+ options: '--atoms 12 --seed 42 --max_iterations 100'
+
+ - files: ['datasets/pendigits.csv']
+ options: '--atoms 12 --seed 42'
+
+ - files: ['datasets/pendigits.csv']
+ options: '--atoms 12 --seed 42 --normalize'
+
+ - files: ['datasets/pendigits.csv']
+ options: '--atoms 12 --seed 42 --lambda1 0.01 --lambda2 0.005'
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