improving music mood classification using lyrics, audio and social tags

selected. The 17 text statistic features defined in Table 6.2 are denoted as “TextStats” in Table
6.7. These statistics were kept unchanged in this experiment, because the 17 dimensions of them
were already compact compared to the 134 interjection words and punctuations. Since the SVM
is used as the classifier, and a previous study (Yu, 2008) suggested feature selection using SVM
ranking worked best for SVM classifiers, the punctuation marks and interjection words were
ranked according to the feature weights calculated by the SVM classifier. Like all experiments in
this research, the results were averaged across a 10-fold cross validation, and the feature ranking
and selection was performed only using the training data in each fold. The results in Table 6.7
show that many of the interjection words and punctuation marks are redundant indeed. And this
is how the 25 TextStyle features in Table 6.2 were determined.
To provide a sense of how the top features distributed across the positive and negative
samples of the categories, the distributions for each of the 25 TextStyle features (six interjection
words, two special punctuations and 17 text statistics) were plotted. Figure 6.1, Figure 6.2 and
Figure 6.3 illustrate the distributions of three sample features: “hey,” “!,” and
“numberOfWordsPerMinute.”
In these figures, the categories are in descending order of the number of songs in each
category. As can be seen in the figures, the positive and negative bars for each category generally
have uneven heights. The greater the differences, the more distinguishing power the feature
would have for that category.
85