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Table 7 The results of different dimensions on medical code classification between our method and Word2Vec

From: Refining electronic medical records representation in manifold subspace

Dimension

Metric

Word2Vec

Ours

100

Pearson

69.2

68.8

100

Spearman

63.8

63.5

200

Pearson

69.2

70.1

200

Spearman

63.8

64.3

250

Pearson

69.2

71.2

250

Spearman

63.8

65.6

300

Pearson

69.2

70.8

300

Spearman

63.8

67.3

  1. Bold values represent the best result for each row of data(%). (Original space dimension is 300d,(window start \(\in\) [0,1000], number of MLLE local neighbors = 500, manifold dimensionality = space dimensionality)
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BMC Bioinformatics

ISSN: 1471-2105

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