Your wekaExperiment example report
2015-11-16
Experiment: weka
- Methods: J48, NaiveBayes, OneR, RandomForest
- Problems: anneal, audiology, balance-scale, car, glass, horsecolic, hypothyroid, ionosphere, liver-disorders, lymph, primary-tumor, soybean, vehicle, vote, vowel
- Parameters:
- featureSelection [no,yes] (instantiated)
- Outputs: accuracy, trainingTime
History:
- Experiment weka loaded from a data set.
- Parameters 'fold' have been removed using the function 'mean'
- A set of pairs 'column:[defaultValues]' has been used to subset the experiment: featureSelection:[no]
- Methods has been instanciated with the parameters: featureSelection
Experiment: weka
- Methods: NaiveBayes, J48, RandomForest, OneR
- Problems: hypothyroid, liver-disorders, vehicle, car, ionosphere, soybean, vote, anneal, lymph, vowel, audiology, glass, primary-tumor, balance-scale, horsecolic
- Parameters:
- featureSelection [no,yes]
- fold [0,1,2,3,4,5,6,7,8,9]
- Outputs: accuracy, trainingTime
History:
- Experiment weka loaded from a data set.
Experiment: weka
- Methods: J48, NaiveBayes, OneR, RandomForest
- Problems: anneal, audiology, balance-scale, car, glass, horsecolic, hypothyroid, ionosphere, liver-disorders, lymph, primary-tumor, soybean, vehicle, vote, vowel
- Parameters:
- nuevoPar [nuevoVal]
- featureSelection [no,yes] (instantiated)
- Outputs: accuracy, trainingTime
History:
- Experiment weka loaded from a data set.
- Parameters 'fold' have been removed using the function 'mean'
- A set of pairs 'column:[defaultValues]' has been used to subset the experiment: featureSelection:[no]
- Methods has been instanciated with the parameters: featureSelection
- New parameters have been added with default values: nuevoPar:nuevoVal
Friedman Test for output "accuracy"
From experiment:
weka
Friedman test for output accuracy
- H0: all methods being equivalent.
- H1: at least one method is not equivalent.
- Strategy for ranks: maximize
- Computed Chi squared statistic with 3 degrees of freedom: 20.84
- Computed p-value: 0.000113645596289616
- Outcome for α = 0.05: H0 Rejected
Results for output "accuracy"
From experiment:
weka
Cumulative Ranking for Var accuracy
From experiment:
weka
Summary of Control post-hoc test for output "accuracy"
From experiment:
weka
- Test: Control post-hoc test
- Adjust Method: Holm
- α = 0.05
- Boldfaced results represent non-rejected hipotheses
| method | pvalue | rank | win | tie | loss |
| RandomForest | - | 1.67 | - | - | - |
| J48 | 5.7161e-01 | 1.93 | 9 | 0 | 6 |
| NaiveBayes | 3.2419e-02 | 2.80 | 11 | 0 | 4 |
| OneR | 1.2329e-04 | 3.60 | 15 | 0 | 0 |
\begin{tabular}{lrrrrr}
\hline
method & pvalue & rank & win & tie & loss\\
\hline
RandomForest & - & 1.67 & - & - & -\\
J48 & \bf 5.7161e-01 & 1.93 & 9 & 0 & 6\\
NaiveBayes & 3.2419e-02 & 2.80 & 11 & 0 & 4\\
OneR & 1.2329e-04 & 3.60 & 15 & 0 & 0\\
\hline
\end{tabular}
Distribution of ranks for output "accuracy"
From experiment:
weka
Detailed results for output(s) "accuracy"
From experiment:
weka
| method | anneal | audiology | balance-scale | car | glass | horsecolic | hypothyroid | ionosphere | liver-disorders | lymph | primary-tumor | soybean | vehicle | vote | vowel |
| J48 | 98.7753 | 75.2964 | 75.7143 | 77.8861 | 66.8831 | 85.3228 | 99.4167 | 87.4762 | 61.8151 | 77.0476 | 40.7041 | 82.4020 | 73.1555 | 96.9979 | 52.2222 |
| NaiveBayes | 86.5281 | 68.6561 | 87.8469 | 73.1352 | 44.5022 | 78.2357 | 95.4142 | 79.4682 | 49.3025 | 82.4762 | 50.7308 | 88.4165 | 44.4314 | 89.6564 | 59.6970 |
| OneR | 83.6330 | 46.5613 | 36.3543 | 70.0081 | 53.8312 | 81.5165 | 96.3415 | 78.3413 | 53.0420 | 74.2857 | 25.3298 | 24.9126 | 52.6050 | 95.6184 | 26.3636 |
| RandomForest | 99.1074 | 71.7786 | 79.7031 | 81.8780 | 77.6191 | 84.2117 | 99.3106 | 93.7460 | 64.0924 | 79.1428 | 40.6952 | 84.7506 | 73.0434 | 96.5380 | 64.6465 |
\begin{tabular}{lrrrrrrrrrrrrrrr}
\hline
method & anneal & audiology & balance-scale & car & glass & horsecolic & hypothyroid & ionosphere & liver-disorders & lymph & primary-tumor & soybean & vehicle & vote & vowel\\
\hline
J48 & 98.7753 & \bf 75.2964 & 75.7143 & 77.8861 & 66.8831 & \bf 85.3228 & \bf 99.4167 & 87.4762 & 61.8151 & 77.0476 & 40.7041 & 82.4020 & \bf 73.1555 & \bf 96.9979 & 52.2222\\
NaiveBayes & 86.5281 & 68.6561 & \bf 87.8469 & 73.1352 & 44.5022 & 78.2357 & 95.4142 & 79.4682 & 49.3025 & \bf 82.4762 & \bf 50.7308 & \bf 88.4165 & 44.4314 & 89.6564 & 59.6970\\
OneR & 83.6330 & 46.5613 & 36.3543 & 70.0081 & 53.8312 & 81.5165 & 96.3415 & 78.3413 & 53.0420 & 74.2857 & 25.3298 & 24.9126 & 52.6050 & 95.6184 & 26.3636\\
RandomForest & \bf 99.1074 & 71.7786 & 79.7031 & \bf 81.8780 & \bf 77.6191 & 84.2117 & 99.3106 & \bf 93.7460 & \bf 64.0924 & 79.1428 & 40.6952 & 84.7506 & 73.0434 & 96.5380 & \bf 64.6465\\
\hline
\end{tabular}