Authorship Attribution Using the Chaos Game Representation
Table 5: Results in percents for AA and genre classification for the Brazilian newspaper data set. The results of the proposed methods using LR and FTT+PCA options are presented beside results presented by other methods in the literature. For the proposed methods, percents for cases when the correct author is second and 3rd or 4th respectively are also shown.
['Chosen', 'Correct', 'Next', '3rd or 4th', 'Genre']
The testing proceeds as follows. The FTT+PCA method had settings to retain the lowest 100x100 submatrix of Fourier frequencies, and the largest 28 singular values and corresponding right singular vectors. For each processed text image, the 12 closest neighbors are found. A score for the classifier is constructed, as before, based on reciprocal distances between neighbors and test vector. The prospective author with top score is the main guess. In 63.3% of the tests this guess is in fact the correct author. Another 12.2% have the correct author as second highest scoring prospective author. Nearly 9% of the correct authors are found amongst the third and fourth highest scoring prospective authors. Loosely, nearly 85% of the test cases have authors in the top four guesses. As it can be observed, for the LR method the results are even better. Again each test can be ascribed to any of 100 different authors, and this classifier ascribes an internal probability to each author for a given test image. In 82% of the test cases the correct author is in fact the one that the classifier has identified as having the highest probability. Moreover, in 93% of the tests, the correct author lies amongst the top four candidates. Not surprisingly the correctness percentages go up. With the FTT+PCA method the correct genre is identified in 82.5% of the tests, with the second guess being the correct genre in another 9.25% of the test cases. LR correctly identifies genre in 86.8% of the tests, with another 9.2% having the correct genre as second best guess.