This book introduces the CAML model, a novel integration of Cellular Automata (CA) and Machine Learning (ML), designed to deliver efficient computation with minimal training data and low computing resources. CAML operates through two key perspectives: one where CA is enhanced by ML to handle complex non-linear evolution, and another where CA strengthens ML by leveraging linear CA evolution to process linear functions effectively. The book focuses on real-world applications of CA, such as in Computational Biology, where CAML models protein chains to predict mutations linked to human diseases, using carefully designed CA rule sequences for each amino acid. Another significant application is in multi-language Sentiment Analysis, where the model analyzes text in five languages (Hindi, Arabic, English, Greek, and Georgian), without relying on pre-trained language models. The input data, used in the experiment, is generated using Python library Scikit-learn and are defined as n-bit binary strings.

New Kind of Machine Learning-Cellular Automata Model PDF

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