m-pana / avila

Analysis of the Avila bible dataset from the UCI repository using several machine learning algorithms.

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A digital approach to palaeography

An extensive analysis of the Avila dataset. The goal is to identify which scribe is the author of a certain pattern based on the available attributes.

Algorithms employed include:

  • QDA
  • SVM
  • Logistic Regression
  • Ridge classifier
  • k-NN
  • Random forest

and others.

To shorten computation times and to ease the illustration of the behavior of certain algorithms, the study is restricted to the patterns associated to 6 out of the 12 scribes.

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Analysis of the Avila bible dataset from the UCI repository using several machine learning algorithms.

License:MIT License


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