  Machine Learning (ML) helps us to recognize patterns from raw data. ML is
used in numerous domains i.e. biomedical, agricultural, food technology, etc.
Despite recent technological advancements, there is still room for substantial
improvement in prediction. Current ML models are based on classical theories of
probability and statistics, which can now be replaced by Quantum Theory (QT)
with the aim of improving the effectiveness of ML. In this paper, we propose
the Binary Classifier Inspired by Quantum Theory (BCIQT) model, which
outperforms the state of the art classification in terms of recall for every
category.
