From 53b58b85d231b1277664d6f68fa73940de584212 Mon Sep 17 00:00:00 2001 From: pagutierrez Date: Sat, 20 Jan 2018 13:36:37 +0100 Subject: [PATCH] Included ESL data --- doc/orca-tutorial.md | 6 +- exampledata/ESL.csv | 488 +++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 491 insertions(+), 3 deletions(-) create mode 100644 exampledata/ESL.csv diff --git a/doc/orca-tutorial.md b/doc/orca-tutorial.md index c969830..09a44b8 100644 --- a/doc/orca-tutorial.md +++ b/doc/orca-tutorial.md @@ -106,7 +106,7 @@ title('AMAE performance (smaller is better)') *** Exercise *** : you should repeat this barplots but considering: - One `global` (i.e. a metric where the class a priori probability is not considered) **nominal** metric. -- One `global` **ordinal** metric. +- One `global` **ordinal** metric. - One **nominal** metric specifically designed for imbalanced datasets. - One **ordinal** metric specifically designed for imbalanced datasets. @@ -531,9 +531,9 @@ end ``` The source code of this example is in [exampleERAHHoldout.m](../src/code-examples/exampleERAHHoldout.m). As can be checked, the `cvpartition` function performs the partitions, receiving the target vector. The targets are used in order to obtain a stratified partition. -*** Exercise *** : you should prepare a `30holdout` set of partitions for the dataset `ESL`, which is included in the [exampledata](/exampledata). Try to find the differences between this dataset and ERA. +*** Exercise *** : you should prepare a `30holdout` set of partitions for the dataset `ESL`, which is included in the folder [exampledata](/exampledata). Try to find the description of this dataset in the Internet and spot the main differences with respect to ERA. -*** Exercise *** : compare the results obtained for `ERA` and `ESL` datasets using the same experimental design you used in the [experiment section](orca-tutorial.md#launch-experiments-through-ini-files). Generate bar plots for comparing accuracy and AMAE. +*** Exercise *** : train classifiers for both `ERA` and `ESL` datasets, using the same experimental design you used in the [experiment section](orca-tutorial.md#launch-experiments-through-ini-files). Compare the results obtained for both datasets. Generate bar plots for comparing accuracy and AMAE. Which one is better classified? Which one is better ordered? ### Warning about highly imbalanced datasets diff --git a/exampledata/ESL.csv b/exampledata/ESL.csv new file mode 100644 index 0000000..4ebd708 --- /dev/null +++ b/exampledata/ESL.csv @@ -0,0 +1,488 @@ +5.0 4.0 3.0 2.0 1 +3.0 2.0 2.0 6.0 1 +2.0 1.0 2.0 4.0 2 +4.0 2.0 3.0 4.0 2 +2.0 2.0 2.0 4.0 2 +2.0 1.0 4.0 4.0 2 +3.0 4.0 4.0 3.0 2 +2.0 1.0 3.0 4.0 2 +2.0 1.0 4.0 5.0 2 +5.0 3.0 2.0 2.0 2 +2.0 2.0 3.0 4.0 2 +6.0 3.0 4.0 5.0 3 +4.0 3.0 4.0 6.0 3 +4.0 3.0 3.0 5.0 3 +4.0 3.0 3.0 5.0 3 +4.0 4.0 3.0 3.0 3 +4.0 2.0 4.0 5.0 3 +2.0 3.0 5.0 4.0 3 +3.0 1.0 4.0 4.0 3 +4.0 3.0 3.0 3.0 3 +4.0 5.0 4.0 5.0 3 +3.0 3.0 3.0 5.0 3 +3.0 3.0 4.0 5.0 3 +3.0 3.0 3.0 5.0 3 +2.0 2.0 4.0 5.0 3 +4.0 3.0 3.0 4.0 3 +4.0 5.0 3.0 4.0 3 +4.0 4.0 5.0 5.0 3 +4.0 4.0 5.0 5.0 3 +4.0 4.0 3.0 3.0 3 +2.0 2.0 2.0 5.0 3 +3.0 3.0 5.0 4.0 3 +4.0 3.0 4.0 5.0 3 +7.0 4.0 4.0 5.0 3 +4.0 5.0 3.0 5.0 3 +4.0 3.0 4.0 4.0 3 +5.0 5.0 4.0 4.0 3 +6.0 5.0 4.0 4.0 3 +4.0 3.0 4.0 5.0 3 +4.0 2.0 3.0 4.0 3 +6.0 6.0 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