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MLP Lyrical Analysis

MLP Lyrical Analysis. % of Unique Words # of Unique Words Average Word Length # of Lyrics # of Characters. Input Feature Vectors:. C Application. Traversal of directory in search of lyric data (*.lyr) Parsing and loading lyrics into proper data array structure.

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MLP Lyrical Analysis

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  1. MLP Lyrical Analysis • % of Unique Words • # of Unique Words • Average Word Length • # of Lyrics • # of Characters Input Feature Vectors:

  2. C Application • Traversal of directory in search of lyric data (*.lyr) • Parsing and loading lyrics into proper data array structure. • Filtering of data skewing characters. • Analysis to extract needed characteristics of lyrics • Output into file with proper format for MLP program.

  3. MLP Development • Normalization of Feature Vectors • Optimal solution for # of layers and # of neurons/layer. • Compete Against Baseline Kmeans algorithm (~70%) Rate • Try to achieve a Test Crate nearly as good as Train Crate

  4. Modifications to Original Specification • Study of data input feature vectors to determine correlation with classification. • Changing the size of the ouput classification to improve performance. • Study of different types of data's effectiveness.

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