Github user takuti commented on a diff in the pull request:
https://github.com/apache/incubator-hivemall/pull/107#discussion_r134141649
--- Diff: docs/gitbook/eval/multilabel_classification_measures.md ---
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+<!-- toc -->
+
+# Multi-label classification
+
+
+Multi-label classification problem is the task to predict the labels given
categorized dataset.
+Each sample $$i$$ has $$l_i$$ labels, where $$L$$ is the number of unique
labels in the dataset, and $$0 \leq l_i \leq |L| $$.
+
+This page focuses on evaluation of the results from such multi-label
classification problems.
+
+# Example
+
+For the metrics explanation, this page introduces toy example dataset.
+
+## Data
+
+The following table shows the sample of multi-label classification's
prediction.
+Animal names represent the tags of blog post.
+Left column includes supervised labels,
+Right column includes are predicted labels by a Multi-label classifier.
+
+| truth labels| predicted labels |
+|:---:|:---:|
+|cat, dog | cat, bird |
+| cat, bird | cat, dog |
+| | cat |
+| bird | bird |
+| bird, cat | bird, cat |
+| cat, dog, bird | cat, dog |
+| dog | dog, bird|
+
+
+# Evaluation metrics for multi-label classification
--- End diff --
Much more easier to understand than the explanation of binary
classification ð
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